DYNAMIC 129Xe GAS EXCHANGE SPECTROSCOPY

ABSTRACT

Methods and systems with  129 Xe dynamic spectroscopy with a fitting function that includes one or more non-Lorentzians, optionally with a barrier Voigt, and signal processing for identifying cardiogenic oscillations for evaluating disease states, use in drug discovery or monitoring disease status.

RELATED APPLICATIONS

This application claims the benefit of and priority to U.S. ProvisionalApplication Ser. No. 62/673,175 filed May 18, 2018, the contents ofwhich are hereby incorporated by reference as if recited in full herein.

GOVERNMENT GRANTS

The invention was made with government support under Grant Numbers NHLB1R01 HL105643 and NHLBI R01HL126771 awarded by the National Institutes ofHealth and under Grant Number HHSN268201700001C awarded by theDepartment of Health and Human Services. The United States governmenthas certain rights in the invention.

RESERVATION OF COPYRIGHT

A portion of the disclosure of this patent document contains material towhich a claim of copyright protection is made. The copyright owner hasno objection to the facsimile or reproduction by anyone of the patentdocument or the patent disclosure, as it appears in the Patent andTrademark Office patent file or records, but reserves all other rightswhatsoever.

FIELD OF THE INVENTION

The invention relates to medical evaluations using in vivo NMRspectroscopy.

BACKGROUND

Hyperpolarized (HP) ¹²⁹Xe MRI is emerging as a valuable means of imaginglung structure and function. See Kruger et al. Functional imaging of thelungs with gas agents. Journal of Magnetic Resonance Imaging. 2016;43(2):295-315; Matin et al. Chronic obstructive pulmonary disease: lobaranalysis with hyperpolarized ¹²⁹Xe MR imaging. Radiology. 2016;282(3):857-868. Arguably, its most significant feature as a probe forlung function is related to its solubility in blood and biologicaltissues, combined with distinct in vivo chemical shifts that reflect thelocal environment. See Cherubini et al. Hyperpolarised xenon in biology.Progress in Nuclear Magnetic Resonance Spectroscopy. 2003; 42(1):1-30.¹²⁹Xe dissolved in human blood exhibits separate resonances for redblood cells (RBCs) and plasma, separated by approximately 22 ppm. SeeNorquay et al. ¹²⁹Xe chemical shift in human blood and pulmonary bloodoxygenation measurement in humans using hyperpolarized 129Xe NMR.Magnetic resonance in medicine. 2017; 77(4):1399-1408; Wolber et al.Hyperpolarized ¹²⁹Xe NMR as a probe for blood oxygenation. Magneticresonance in medicine. 2000; 43(4):491-496. ¹²⁹Xe spectra acquired inthe human lung also exhibit a unique RBC peak at 217 ppm, relative tothe gas-phase resonance at 0 ppm, as well as a resonance consisting of¹²⁹Xe dissolved in both plasma and parenchymal tissues. See Kaushik etal. Measuring diffusion limitation with a perfusion-limitedgas-hyperpolarized 129Xe gas-transfer spectroscopy in patients withidiopathic pulmonary fibrosis. Journal of Applied Physiology. 2014;117(6):577-585. Because these environments also form the barrier todiffusive ¹²⁹Xe or O₂ transfer to RBCs, it is often termed the barrierresonance. See Cleveland et al. 3D MRI of impaired hyperpolarized ¹²⁹Xeuptake in a rat model of pulmonary fibrosis. NMR in Biomedicine. 2014;27(12):1502-1514. Although recent high resolution spectroscopy suggeststhat the barrier resonance may contain additional structure, it isgenerally considered to have a frequency shift of about 198 ppm. SeeRobertson et al. Uncovering a third dissolved-phase ¹²⁹Xe resonance inthe human lung: Quantifying spectroscopic features in healthy subjectsand patients with idiopathic pulmonary fibrosis. Magnetic resonance inmedicine. 2017; 78(4):1306-1315. The contents of the cited documents arehereby incorporated by reference as if recited in full herein.

Recently, these unique spectroscopic properties of ¹²⁹Xe have beenexploited to yield 3D images of pulmonary gas exchange. See Qing et al.Regional mapping of gas uptake by blood and tissue in the human lungusing hyperpolarized xenon-129 MRI. Journal of Magnetic ResonanceImaging. 2014; 39(2):346-359. Such imaging has revealed impaired gasexchange in various diseases affecting the cardiopulmonary system. Inpatients with idiopathic pulmonary fibrosis (IPF), for example, ¹²⁹Xeuptake in the barrier is significantly enhanced throughout much of thelung, while its transfer to RBCs is focally impaired. See Wang et al.,Using hyperpolarized ¹²⁹Xe MRI to quantify regional gas transfer inidiopathic pulmonary fibrosis. Thorax. 2017:thoraxjnl-2017-210070. Bycontrast, in the setting of COPD with emphysema, both barrier uptake andRBC transfer are diminished. See Wang et al., Quantitative Analysis ofHyperpolarized ¹²⁹Xe Gas Transfer MRI. Medical Physics. 2017. Moreover,¹²9Xe gas exchange MRI has recently demonstrated impaired RBC transferin pulmonary vascular disease. See Dahhan et al., Abnormalities inhyperpolarized 129Xe magnetic resonance imaging and spectroscopy in twopatients with pulmonary vascular disease. Pulmonary circulation. 2016;6(1):126-131. The contents of the documents cited in the Background arehereby incorporated by reference as if recited in full herein.

Patients can present with wide range of co-morbidities such asasthma-COPD overlap syndrome (ACOS), combined fibrosis and emphysema(CPFE), or secondary pulmonary hypertension (PH), and it can beimportant to differentiate the underlying pathophysiologies responsiblefor impaired gas exchange.

Pulmonary vascular diseases (PVD), such as pulmonary arterialhypertension (PAH) and pulmonary venoocclusive disease (PVOD) cause anobstruction of blood flow through the lung vasculature that results inright heart failure. Even with current therapies, PVD is associated withsubstantial morbidity and mortality, with 5-year survival only˜50%.However, the management of PVD is significantly limited by the criteriafor its diagnosis as well as non-invasive methods of monitoring disease.The most common PVD, PAH can be diagnosed only by invasive right heartcatheterization (RHC). Moreover, it requires meeting specifichemodynamic and clinical criteria: pulmonary hypertension (PH), definedas a mean pulmonary artery pressure (mPAP)≥25 mmHg, with a pulmonarycapillary wedge pressure (PCWP)≤15 mmHg in the absence of significantheart, lung or specific systemic diseases. Other PVD is either diagnosedby pathology or exclusion. These strict criteria may exclude patientswho actually have the pathologic lesions of PVD that could potentiallybenefit from treatment with pulmonary vasodilators. For example,patients with diastolic heart failure or lung disease can developsignificant precapillary PH associated with a high pulmonary vascularresistance (PVR). Unfortunately, such secondary causes of increasedresistance typically prevent invasive catheterization from definitivelydiagnosing PVD. Yet this scenario of suspected PVD in patients withconcomitant disease is increasingly common in the aging population.

Thus, there is a need for non-invasive technologies that can aid indiagnosing and/or monitoring pulmonary hypertension and interstitiallung disease including PVD, particularly for many patients who maybenefit from PAH-specific therapies but otherwise will likely remainuntreated.

SUMMARY OF EMBODIMENTS OF THE INVENTION

Embodiments of the present invention provide non-invasive systems andmethods to generate multiple dynamic spectroscopic parameters of the gasexchange region of the lung associated with three different ¹²⁹Xeresonances, a ¹²⁹Xe gas resonance, a ¹²⁹Xe barrier resonance and ¹²⁹Xered blood cells (“RBCs” or “RBC”) resonance.

Embodiments of the invention can provide non-invasive methods andsystems to aid in diagnosing and/or monitoring pulmonary hypertensionand interstitial lung disease including PAH.

Embodiments of the invention can use markers associated with dynamicspectroscopy of ¹²⁹Xe to distinguish between pre-capillary (i.e.,pulmonary arterial hypertension) and post-capillary vasculature disease.

Embodiments of the invention provide disease-specific signature patternscomprising peak-to-peak height values and/or shapes of oscillations ofone or more of RBC amplitude, chemical shift and phase.

The oscillations can be associated with one or more of an inhale,breath-hold and/or exhale time period.

Embodiments of the invention provide a library of disease signaturepatterns that can be useful to diagnose lung diseases or injury, studyor evaluate interstitial lung diseases or injury and/or the progressionor abatement thereof, and/or evaluate the efficacy of directed therapiesthe side effects or the inadvertent negative effects of therapies ordrug treatments and/or drug discovery.

Embodiments of the invention can use ¹²⁹Xe MRI gas-exchange ventilation,barrier and RBC images along with dynamic spectroscopy to distinguishbetween pre-capillary and post capillary vasculature conditions ordisease and/or may, for example, determine how much of a capillary bedis compromised or injured.

Embodiments of the invention can correct and/or adjust RBC oscillationamplitudes by stroke volume and pulmonary exchange volume.

Embodiments of the invention are directed to methods of generatingdynamic spectroscopy parameters. The methods include: obtaining a ¹²⁹Xespectrum of free induction decays (FIDs) ¹²⁹Xe NMR signal of a gasexchange region of a lung or lungs of a subject during a breathingmaneuver comprising one or more of inspiration/inhale, breath-hold andexpiration/exhale; fitting the obtained ¹²⁹Xe spectrum of the FIDs witha curve fitting function; and electronically generating a plurality ofdynamic ¹²⁹Xe spectral parameters based on the fitting. The ¹²⁹Xespectrum is modeled with one or more non-Lorentzian line shapes and theplurality of dynamic ¹²⁹Xe spectral parameters include plots over timeof at least one of: (i) barrier amplitude, barrier chemical shift (ppm),one or more barrier full width at half maximum (FWHM)(ppm) parameters;(ii) gas amplitude, gas chemical shift (ppm), gas FWHM (ppm), and gasphase (degrees); and (iii) red blood cell (RBC) amplitude, RBC chemicalshift (ppm), RBC FWHM (ppm), and RBC phase (degrees).

The method can include, before the fitting and generating steps,extracting temporal variations in ¹²⁹Xe RBC resonance occurring at acardiac frequency.

The fitting can be carried out with a ¹²⁹Xe barrier resonance modeled asa Voigt line shape and with ¹²⁹Xe RBC and ¹²⁹Xe gas-phase resonanceseach modeled using a Lorentzian line shape. The barrier resonance can becharacterized by both a Lorentzian FWHM parameter and a Gaussian FWHM(FWHM_(G)) (ppm) parameter.

The method can further include adjusting amplitude “ApRc” of the RBCamplitude plot by multiplying by: (V_stroke_ref/V_stroke)*(PEV/PEV_ref).V_stroke_ref is a reference stroke volume like 94 ml or 95 ml (adult),V_stroke is a subject's actual stroke volume, PEV_ref is a referencepulmonary exchange volume, and PEV is the subject's measured pulmonaryexchange volume.

The method can further include correcting amplitude of the RBC amplitudeplot of the ¹²⁹Xe spectral parameter for magnetization decays caused byT1 and RF-induced depolarization during a breath-hold period of thebreath-hold of the breathing maneuver by dividing the RBC amplitude “A”by a calculated apparent T1 decay constant (T1app). T1app can bequantified by fitting RBC amplitude over time “t” to Ae^(−t/T1) ^(app) .

The method can further include detrending amplitudes of the ¹²⁹Xespectral parameters, then calculating peak-peak variation over time.

The method can further include calculating temporal changes in signalamplitude of the RBC amplitude (A) as a percentage change from baseline:(rbc_amp_percent):rbc_amp_percent=(rbc_amp−A*exp(−t/T1_(app)))/(A*exp(−t/T1_(app))).T1_(app) is a T1 decay constant and t is time (seconds).

The method can further include calculating temporal changes in signalamplitude of the RBC amplitude (A) using peak to peak analysis of adifference between a maximum and a minimum in an oscillating signal ofthe RBC amplitude.

The method can further include high-pass filtering each of the RBCamplitude, RBC chemical shift, RBC phase and RBC FWHM with a 0.5 Hzcutoff frequency to thereby remove residual baseline variation andprovide filtered parameter plots of the RBC spectral parameters.

The method can further include fitting the filtered parameter plots to asinusoid with phase offset:

½A _(pk-pk) sin(2πf _(c) t+φ),

where A_(pk-pk) is the peak-to-peak amplitude, f_(c) is the cardiacfrequency, t is time in seconds, and φ is a phase off-set, and wheref_(f) is cardiac frequency that is derived from the subject's RBCamplitude oscillations.

f_(c) can be used in temporal fits of all other RBC spectral parameters(chemical shift, linewidth, and phase).

The method can further include normalizing the RBC amplitude spectralparameter, the barrier amplitude spectral parameter and the gasamplitude spectral parameter to a barrier-phase or gas-phase ¹²⁹Xesignal.

The method can further include, before the fitting and generating steps,pre-processing raw FIDs by Fourier Transforming raw data along anindirect time domain with respect to a breath hold time period of thebreath hold of the breathing maneuver, retaining only coefficients thatexceed a defined threshold, then Fourier transforming back along anindirect frequency domain to provide an FID with increased SNR relativeto raw FIDs for the fitting to thereby filter non-dominant frequenciesout of the indirect time domain to smooth temporal changes betweendifferent FIDs, while leaving spectral-frequency domain intact.

The method can further include using a FID sliding boxcar window filterand averaging a plurality of the time domain filtered FIDs to provide anFID with increased SNR for the fitting.

The obtaining can be at least partially in response to a pulse sequencewith a TR in a range of 20 ms-300 ms, and a flip angle of about 20-90degrees to thereby provide increased sensitivity to cardiogenicoscillations.

The obtaining can be at least partially in response to a pulse sequencewith a TR in a range of 200-300 ms and a flip angle in a range of 20-90degrees.

The method can further include providing a plurality of defineddifferent disease pattern signatures of the ¹²⁹Xe spectral parameterscorrelated to different pulmonary hypertension and interstitial lungdiseases.

The method can further include electronically evaluating the generated¹²⁹Xe spectral parameters to identify whether the subject has one ormore of the defined different disease pattern signatures.

The one or more of the defined different disease patterns can includeoscillations of one or more of the RBC spectral parameters that exceedsa defined peak to peak threshold.

The one or more of the defined different disease patterns can includeoscillations of one or more of the RBC spectral parameters that is belowa defined peak to peak threshold.

The one or more of the defined different disease patterns can be basedon a shape of the oscillations of one or more of the ¹²⁹Xe spectralparameters.

The at least one interstitial lung disease can have a disease patternsignature with an RBC frequency shift that decreases during thebreath-hold of the breathing maneuver relative to the inhale and/orexhale portion of the breathing maneuver.

The defined different disease patterns can distinguish pre-capillaryvascular obstruction by diminished RBC amplitude oscillations relativeto a defined norm.

The defined different disease patterns can distinguish post-capillaryvascular disease from pre-capillary vascular disease by increased RBCamplitude oscillations relative to a defined norm.

One or more of the defined different disease patterns can identifycombined pre- and post-capillary vascular disease, optionally by a shapeof the RBC amplitude oscillations.

The method can further include comparing RBC amplitude oscillations ofone or more RBC plot pre and post-administration of a pharmaceuticalagent and identifying vascular reactivity and/or change based on changesin RBC amplitude oscillations.

The pharmaceutical agent can be a vasodilator, optionally thevasodilator is an inhaled vasodilator.

The pharmaceutical agent can include prostacyclin.

The method can further include comparing gas exchange ¹²⁹Xe MRI imagesof the subject to detect pulmonary hypertension associated withdiminished RBC transfer that affects a disproportionately largerfraction of the lung than can be explained by a fraction having abnormalbarrier uptake.

The obtained data can be acquired between every 20 ms to every 300 msduring the breathing maneuver. The breathing maneuver can includebreath-hold, full inspiration and full expiration over a time period of10-30 seconds.

The fitting can be carried out with each resonance characterized by 4spectral parameters: amplitude (α), frequency (f), phase (φ), andLorentzian linewidth (FWHM), and, for the barrier resonance, a 5^(th)parameter, a Gaussian linewidth (FWHM_(G)), is also extracted, whereinthe fitting is carried out with the barrier resonance initialized withequal Lorentzian and Gaussian linewidths, and wherein the fitting iscarried out using the below equation:

$\begin{matrix}{s_{fit} = {{a_{rbc}e^{{i\; \phi_{r\; {bc}}} + {2\; \pi \; {if}_{rbc}t}}e^{{- \pi}\; t \times {FWHM}_{rbc}}} + {a_{bar}e^{{i\; \phi_{bar}} + {2\; \pi \; {if}_{bar}t}}e^{{- \pi}\; t \times {FWHM}_{bar}}e^{{- 4}\; l\; n\; 2 \times t^{2}{FWHM}_{G_{bar}^{2}}}} + {a_{gas}e^{{i\; \phi_{gas}} + {2\; \pi \; i\; f_{gas}t}}e^{{- \pi}\; t\; \times {FWHM}_{gas}}}}} & {{EQN}(1)}\end{matrix}$

The method can further include identifying whether the subject has IPF,wherein IPF can be characterized by a disease signature pattern with RBCamplitude oscillations that are significantly larger (at least about1.25× or 1.5× larger) than a healthy cohort, and the RBC frequency(chemical shift/ppm) and phase oscillations are at least 1.5×, typicallyat least 2× above a healthy cohort.

The RBC amplitude variations can be at least 1.5 fold greater than ahealthy cohort (optionally 16.8±5.2% vs 9.7±2.9%; P=0.008), the chemicalshift oscillations are more than 5-fold higher than the healthy cohort(optionally 0.43±0.33 ppm vs 0.083±0.05 ppm; P<0.001), and the RBC phaseoscillations are more than 5-fold higher than the healthy cohort(optionally 7.7±5.6° vs 1.4±0.8°; P<0.001).

The method can further include transmitting the obtained data from animaging site with an MR Scanner to a remote server. The remote servercan perform the fitting and generating actions. The remote server caninclude or be in communication with a database of defined differentdisease pattern signatures of the ¹²⁹Xe spectral parameters correlatedto pulmonary hypertension and interstitial lung diseases.

The method can further include obtaining a plurality of ¹²⁹Xe imagingparameters of the lung or lungs of the subject including at least two ofRBC defect percentage, ventilation defect percentage and barrier defectpercentage; and identifying whether the patient has a cardiopulmonarydisease based on the obtained ¹²⁹Xe imaging parameters and at least twoof the plurality of the dynamic ¹²⁹Xe spectral parameters.

IPF can be characterized by a disease signature pattern comprising anRBC chemical shift (ppm) that is below 217 ppm.

A method of identifying a cardiopulmonary disease of a patient,comprising: obtaining a plurality of ¹²⁹Xe imaging parameters includingred blood cell (RBC) defect percentage, ventilation defect percentageand barrier defect percentage; obtaining a plurality of ¹²⁹Xe dynamicspectroscopy parameters including RBC shift oscillation and RBCamplitude oscillation; and identifying whether the patient has acardiopulmonary disease based on the obtained ¹²⁹Xe imaging parametersand the ¹²⁹Xe dynamic spectroscopy parameters.

The method can further include generating a graphic signature of patientcardiopulmonary health or disease state based on the obtained ¹²⁹Xeimaging parameters and the ¹²⁹Xe dynamic spectroscopy parameters, thenidentifying whether the patient has a cardiopulmonary disease based onthe generated graphic signature.

The method can further include comparing the generated graphic signatureto a library of graphic signatures which comprises unique graphicsignatures for each of: chronic obstructive pulmonary disease (COPD),idiopathic pulmonary fibrosis (IPF), left heart failure (LHF), andpulmonary arterial hypertension (PAH).

The method can further include providing a diagnostic model that definesa likelihood of different diseases based on different thresholds ofpeaks of RBC oscillation and peaks of chemical shift (ppm) oscillation.The identifying can be carried out using the provided diagnostic model.

Yet other embodiments are directed to an MRI scanner system thatincludes an MRI scanner comprising a MRI receiver and at least oneprocessor in communication with the MRI scanner and configured to carryout any of the methods of the present invention.

Other embodiments are directed to a medical evaluation system thatincludes a server in communication with at least one MRI scanner andhaving at least one processor that carries out any of the methods of thepresent invention.

Although described herein with respect to method aspects of the presentinvention, it will be understood that the present invention may also beembodied as systems and computer program products.

Other systems, methods, and/or computer program products according toembodiments of the invention will be or become apparent to one withskill in the art upon review of the following drawings and detaileddescription. It is intended that all such additional systems, methods,and/or computer program products be included within this description, bewithin the scope of the present invention, and be protected by theaccompanying claims.

BRIEF DESCRIPTION OF THE DRAWINGS

The patent or application file contains at least one drawing executed incolor. Copies of this patent or patent application publication withcolor drawings will be provided by the Office upon request and paymentof the necessary fee.

Features of the present invention will be more readily understood fromthe following detailed description of exemplary embodiments thereof whenread in conjunction with the accompanying drawings.

FIG. 1 are plots/graphs of temporal changes in spectroscopic parametersof the ¹²⁹Xe gas (left side graphs), barrier (middle graphs) and RBC(right side graphs) resonances (normalized) in a representative healthysubject during inhalation, breath hold and exhalation according toembodiments of the present invention.

FIG. 2 are plots/graphs of temporal changes in spectroscopic parametersof the ¹²⁹Xe gas (left side graphs), barrier (middle graphs) and RBC(right side graphs) resonances (normalized) in a representative subjectwith IPF during inhalation, breath hold and exhalation according toembodiments of the present invention

FIG. 3 are plots/graphs of normalized and detrended RBC spectralparameter over time (“dynamics”) during a breath hold from a healthysubject (left side graphs), two subjects with IPF, two subjects with PAHand two subjects with LHF, according to embodiments of the presentinvention.

FIGS. 4A-4D are plots/graphs that compare peak-to-peak cardiogenicoscillations in RBC spectral parameters during a breath hold for healthyversus IPF subjects according to embodiments of the present invention.FIG. 4A compares peak-to-peak RBC amplitude oscillations (percent). FIG.4B compares peak-to-peak RBC FWHM oscillations (ppm). FIG. 4C comparespeak-to-peak RBC chemical shift oscillations (ppm). FIG. 4D comparespeak-to-peak RBC phase (degrees) oscillations.

FIGS. 5A-5D are plots/graphs that compare oscillations in RBC spectralparameters for healthy versus IPF and PAH cohorts/subjects according toembodiments of the present invention. FIG. 5A compares peak-to-peak RBCamplitude oscillations (percent).

FIG. 5B compares peak-to-peak RBC FWHM oscillations (ppm). FIG. 5Ccompares peak-to-peak RBC chemical shift oscillations (ppm). FIG. 5Dcompares peak-to-peak RBC phase (degrees) oscillations.

FIG. 6A are graphs of dissolved phase fits for a large average of FIDswith minimal residual error for the 3-Lorentzian model (left side) andbarrier Voigt model (left side) according to embodiments of the presentinvention.

FIG. 6B are graphs that illustrate dynamically acquired spectroscopy fora healthy volunteer which returns poor condition fits for the barrierresonances in the 3-Lorentizian model (left and middle set of panels),which is overcome by the barrier Voight model (right most panels)according to embodiments of the present invention.

FIG. 7A is set of color-coded ¹²⁹Xe MRI images for a COPD patient withsevere ventilation defects (ventilation images top two rows) but withbarrier uptake (middle two rows) and RBC uptake (bottom two rows)relatively well-matched according to embodiments of the presentinvention.

FIG. 7B is set of color-coded ¹²⁹Xe MRI images for a COPD patient(ventilation images top two rows) with barrier uptake (middle two rows)and RBC uptake (bottom two rows) showing RBC transfer defectsdisproportionately worse than barrier uptake suggesting possiblepre-capillary pulmonary hypertension according to embodiments of thepresent invention.

FIG. 8A is a flow chart of actions that can be used to carry outembodiments of the present invention.

FIG. 8B is a flow chart of actions that can be used to carry outembodiments of the present invention.

FIG. 8C is a flow chart of actions that can be used to carry outembodiments of the present invention.

FIG. 8D is a flow chart of actions that can be carried out to adjust RBCamplitude oscillation values according to embodiments of the presentinvention.

FIG. 9 is a block diagram of data processing systems that may be used toidentify different disease states using defined signatures of multiple¹²⁹Xe spectroscopic parameters associated with oscillations of RBCand/or barrier plots accordance with some embodiments of the presentinvention.

FIG. 10 is a schematic illustration of a medical evaluation system incommunication with an MRI imaging system according to embodiments of thepresent invention.

FIG. 11 is a block diagram of data processing systems according toembodiments of the present invention.

FIGS. 12A-12D are plots of comparisons of static parameters for healthyand IPF subjects during a first second of a breath-hold with RBC phaseset to zero degrees according to embodiments of the present invention.FIG. 12A (left panels) illustrates RBC chemical shift (ppm), FWHM (ppm),FWHM_(G) (ppm), and phase (degrees). FIG. 12B illustrates barrierchemical shift (ppm), FWHM (ppm), FWHM_(G) (ppm), and phase (degrees).FIG. 12C illustrates a derived metric of RBC:barrier ratio. FIG. 12Dillustrates a derived metric of RBC-barrier frequency difference forchemical shift (ppm) (i.e., the difference in chemical shift between theRBC and barrier peak) according to embodiments of the present invention.

FIG. 13 are normalized and detrended RBC spectral parameter dynamicsduring a breath hold from a representative healthy volunteer (left sidepanels) and 5 subjects with IPF according to embodiments of the presentinvention. The solid line represents a sinusoidal fit.

FIG. 14 is a table of subject demographics, pulmonary function test(PFT) results, and RBC oscillation information according to embodimentsof the present invention.

FIG. 15 is a table of demographic and clinical characteristicsstratified by condition according to embodiments of the presentinvention.

FIG. 16 is set of color-coded ¹²⁹Xe MRI images (maps) for ofrepresentative subjects from each cohort (healthy, COPD, IPF, LHF andPAH), with ventilation mages top rows, barrier middle row and RBCuptake/transfer bottom row according to embodiments of the presentinvention.

FIG. 17A is a graph of ventilation defect percentage for healthy anddifferent disease cohorts according to embodiments of the presentinvention.

FIG. 17B is a graph of RBC defect percentage for healthy and differentdisease cohorts according to embodiments of the present invention.

FIG. 17C is a graph of Barrier defect percentage for healthy anddifferent disease cohorts according to embodiments of the presentinvention.

FIG. 17D is a graph of Barrier high percentage for healthy and differentdisease cohorts according to embodiments of the present invention.

FIG. 18A is a graph of RBC A amplitude (%) over time (s) for healthy anddifferent disease cohorts according to embodiments of the presentinvention.

FIG. 18B is a graph of RBC A shift (ppm) over time (s) for healthy anddifferent disease cohorts according to embodiments of the presentinvention.

FIG. 19A is a graph of RBC amplitude oscillations (%) versus healthy anddifferent disease cohorts according to embodiments of the presentinvention.

FIG. 19B is a graph of RBC shift oscillations (ppm) versus healthy anddifferent disease cohorts according to embodiments of the presentinvention.

FIG. 20 is an illustration of a conceptual model depicting diseasephenotypes at an alveolar-capillary interface and biomarker parametersaccording to embodiments of the present invention.

FIG. 21 is a set of radar plots illustrating ¹²⁹Xe disease state andhealthy signatures for patients with COPD, IPF, LHF and PAH based on¹²⁹Xe imaging and spectroscopic parameters/markers according toembodiments of the present invention.

FIG. 22 are representative of ventilation, barrier and RBC images andassociated amplitude and chemical shift spectra of healthy lungsaccording to embodiments of the present invention.

FIG. 23 are representative of ventilation, barrier and RBC images andassociated amplitude and chemical shift spectra of a subject with PAHaccording to embodiments of the present invention.

FIG. 24 are representative of ventilation, barrier and RBC images andassociated amplitude and chemical shift spectra of a subject with ILDaccording to embodiments of the present invention.

FIG. 25 is a graph of RBC amplitude oscillation (%) for healthy anddifferent disease states of the lung(s) according to embodiments of thepresent invention.

FIG. 26 is a graph of True Positive Rate versus False Positive Rateusing ROC curve of RBC amplitude oscillation according to embodiments ofthe present invention.

FIG. 27 is a set of 3D images (ventilation, barrier and RBC) of healthyand different disease cohorts illustrating metrics that can furtherdistinguish the different disease cohorts according to embodiments ofthe present invention.

FIG. 28 is a schematic illustration of a diagnostic analysis protocol ofdefined parameters that can be used to identify a disease stateaccording to embodiments of the present invention.

FIG. 29 is an example application of image and spectra metric parametersof Subject A that can be used for a diagnostic analysis protocolaccording to embodiments of the present invention.

FIG. 30 illustrates the diagnostic analysis applied to the metricparameters of Subject A according to embodiments of the presentinvention.

FIG. 31 is an example application of image and spectra metric parametersof Subject B that can be used for a diagnostic analysis protocolaccording to embodiments of the present invention.

FIG. 32 illustrates the diagnostic analysis applied to the metricparameters of Subject B according to embodiments of the presentinvention.

DETAILED DESCRIPTION OF EMBODIMENTS OF THE INVENTION

While the invention may be made in modified and alternative forms,specific embodiments thereof are shown by way of example in the drawingsand will be described in detail. It should be understood, however, thatthere is no intent to limit the invention to the particular formsdisclosed, but on the contrary, the invention is to cover allmodifications, equivalents, and alternatives falling within the spiritand scope of the invention. Like reference numbers signify like elementsthroughout the description of the figures.

In the figures, the thickness of certain lines, layers, components,elements or features may be exaggerated for clarity. Broken linesillustrate optional features or operations unless specified otherwise.The sequence of operations (or steps) is not limited to the orderpresented in the claims or figures unless specifically indicatedotherwise.

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting of the invention. Asused herein, the singular forms “a”, “an” and “the” are intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. It will be further understood that the terms “comprises”and/or “comprising,” when used in this specification, specify thepresence of stated features, integers, steps, operations, elements,and/or components, but do not preclude the presence or addition of oneor more other features, integers, steps, operations, elements,components, and/or groups thereof. As used herein, the term “and/or”includes any and all combinations of one or more of the associatedlisted items. As used herein, phrases such as “between X and Y” and“between about X and Y” should be interpreted to include X and Y. Asused herein, phrases such as “between about X and Y” mean “between aboutX and about Y.” As used herein, phrases such as “from about X to Y” mean“from about X to about Y.”

Unless otherwise defined, all terms (including technical and scientificterms) used herein have the same meaning as commonly understood by oneof ordinary skill in the art to which this invention belongs. It will befurther understood that terms, such as those defined in commonly useddictionaries, should be interpreted as having a meaning that isconsistent with their meaning in the context of the specification andrelevant art and should not be interpreted in an idealized or overlyformal sense unless expressly so defined herein. Well-known functions orconstructions may not be described in detail for brevity and/or clarity.

It will be understood that, although the terms first, second, etc. maybe used herein to describe various elements, components, regions, layersand/or sections, these elements, components, regions, layers and/orsections should not be limited by these terms. These terms are only usedto distinguish one element, component, region, layer or section fromanother region, layer or section. Thus, a first element, component,region, layer or section discussed below could be termed a secondelement, component, region, layer or section without departing from theteachings of the present invention.

The term “MRI scanner” refers to a magnetic resonance imaging and/or NMRspectroscopy system. As is well known, the MRI scanners include a lowfield strength magnet (typically between about 0.1 T to about 0.5 T), amedium or a high-field strength super-conducting magnet, an RF pulseexcitation system, and a gradient field system. MRI scanners are wellknown to those of skill in the art. Examples of commercially availableclinical MRI scanners include, for example, those provided by GeneralElectric Medical Systems, Siemens, Philips, Varian, Bruker, Marconi,Hitachi and Toshiba. The MRI systems can be any suitable magnetic fieldstrength, such as, for example, about 1.5 T, and may be higher fieldsystems of between about 2.0 T-10.0 T.

The term “high-field strength” refers to magnetic field strengths above1.0 T, typically above 1.5 T, such as 2.0 T or 3.0 T. However, thepresent invention is not limited to these field strengths and maysuitable for use with higher field strength magnets, such as, forexample, 3.0 T or even greater.

The term “hyperpolarized” ¹²⁹Xe refers to ¹²⁹Xe that has increasedpolarization over natural or equilibrium levels. As is known by those ofskill in the art, hyperpolarization can be induced by spin-exchange withan optically pumped alkali-metal vapor. See Albert et al., U.S. Pat. No.5,545,396; and Cates et al, U.S. Pat. Nos. 5,642,625 and 5,809,801.These references are hereby incorporated by reference as if recited infull herein. One polarizer that is suitable for generating thehyperpolarized ¹²⁹Xe is the 9800, 9810 or 9820 polarizer models made byPolarean, Imaging, plc, Durham, N.C. Thus, as used herein, the terms“hyperpolarize”, “polarize”, and the like mean to artificially enhancethe polarization of certain noble gas nuclei over the natural orequilibrium levels.

The term “automatically” means that the operation can be substantially,and typically entirely, carried out without human or manual input, andis typically programmatically directed or carried out. The term“electronically” includes both wireless and wired connections betweencomponents. The term “programmatically” means under the direction of acomputer program that communicates with electronic circuits and otherhardware and/or software.

The term “3-D image” refers to visualization in 2-D what appear to be3-D images using volume data that can represent features with differentvisual characteristics such as with differing intensity, opacity, color,texture and the like. For example, the 3-D image of the lung can begenerated to illustrate differences in barrier thickness using color oropacity differences over the image volume. Thus, the term “3-D” inrelation to images does not require actual 3-D viewability (such as with3-D glasses), just a 3-D appearance in a 2-D viewing space such as adisplay. The 3-D images comprise multiple 2D slices. The 3-D images canbe volume renderings well known to those of skill in the art and/or aseries of 2-D slices, which can be visually paged through.

The term “detrend” and derivatives thereof means adjusting amplitudesignal that decays over the course of a breath hold by correcting forthe apparent T1 relaxation caused by the combination of trueoxygen-induced relaxation and that caused by application of radiofrequency pulses. This flattens the amplitude signal out relative to anon-detrended amplitude signal so that oscillations can be more readilyidentified and/or quantified.

The term “normalize” and derivatives thereof, with respect tooscillations of RBC spectra of the different spectral parameters, meansnormalizing RBC signal by dividing its amplitude by that of anotherspectral parameter (i.e., an amplitude of the barrier or gas-phaseresonance) which can be carried out as normalizing for displaying thedynamics of RBC, barrier and gas, typically before detrending.

Actual RBC oscillation amplitudes can also be “normalized” for aparticular patient/subject, by adjusting for the individual patient'sstroke volume and/or available capillary exchange volume.

The terms “raw data”, “raw FIDs” and “raw NMR signal” refer to thecomplex NMR signal acquired in the time-domain prior to Fouriertransformation.

The term “about” with respect to flip angle means that the number canvary within +/−10%. The term “about” with respect to time means that thestated number can vary is +/−20%. The term “about” with respect toresonance frequency means 2-5 ppm (RBC chemical shift varies from about214.5-219).

As is well known, a basic NMR spectrum line shape has amplitude,chemical shift (sometimes called frequency), linewidth (s), and phase(degrees). FID is a time domain signal (decaying oscillations).Frequency and chemical shift are one and the same. Chemical shift is afrequency referenced to some standard frequency and usually quoted inppm rather than Hz. Similarly, FWHM/linewidth can be given in Hz or ppm.The conversion for FWHM/linewidth from Hz to ppm is carried out bydividing by the ¹²⁹Xe Larmor frequency.

Embodiments of the invention may be particularly suitable for use withhuman patients but may also be used with animals or other mammaliansubjects.

Generally stated, embodiments of the invention obtain and quantifyspectral parameters of hyperpolarized ¹²⁹Xe exchanging in gas exchangeregions of the lung during a breathing maneuver (i.e., protocol)associated with one or all of inhale, breath-hold and exhale. The gasexchange region of the lung includes ¹²⁹Xe gas exchange betweenairspaces, interstitial barrier, and red blood cells (RBCs) which aresensitive to pulmonary pathophysiology. Embodiments of the inventionobtain and evaluate dynamics of ¹²⁹Xe spectroscopy with a particularfocus on quantifying cardiogenic oscillations in the RBC resonance.

As discussed in the Background, the spectral properties of ¹²⁹Xe havebeen well-characterized in vitro and in vivo. The extraordinarysensitivity of ¹²⁹Xe diffusive barrier uptake and RBC transfer to a widerange of pathologies is promising, even as it presents new challenges.Beyond characterizing the static parameters of ¹²⁹Xe gas transferspectra, their temporal dynamics provide an opportunity to gain what maybe additional clinically significant insights. To this end, preliminarywork has reported intriguing observations of cardiac pulsation in theamplitude of the RBC resonance. See Norquay et al. ¹²⁹Xe chemical shiftin human blood and pulmonary blood oxygenation measurement in humansusing hyperpolarized ¹²⁹Xe NMR. Magnetic resonance in medicine. 2017;77(4):1399-1408; and Ruppert et al., Detecting pulmonary capillary bloodpulsations using hyperpolarized xenon-129 chemical shift saturationrecovery (CSSR) MR spectroscopy. Magnetic resonance in medicine. 2015.The contents of these documents are hereby incorporated by referenceherein. However, this work was focused primarily on characterizing ¹²⁹Xeuptake in the alveolar septal unit on the 0-100 ms timescale via thechemical shift saturation recovery (CSSR) method. See Qing et al.,Assessment of lung function in asthma and COPD using hyperpolarized129Xe chemical shift saturation recovery spectroscopy anddissolved-phase MRI. NMR in biomedicine 2014a; 27(12):1490-1501; andStewart et al., Experimental validation of the hyperpolarized 129Xechemical shift saturation recovery technique in healthy volunteers andsubjects with interstitial lung disease. Magnetic resonance in medicine.2015; 74(1):196-207. As such, these studies were limited by relativelylow temporal resolution, did not employ robust curve fitting methods forquantification, and did not investigate the dynamics of other spectralparameters.

While 3D gas exchange MRI provides important ways of characterizing thespatial distribution of gas exchange impairment, it alone may not besufficient to determine the underlying cause. For example, dyspnea canbe caused by interstitial lung disease, or underlying cardiac orpulmonary vascular disease. Even within PVD, it can be difficult todetermine whether obstruction is pre-capillary or post-capillary andthis becomes more difficult in the setting of other lung disease.Moreover, existing methods of evaluating PVD require invasive rightheart catheterization. These problems are uniquely addressednoninvasively, by combining 3D ¹²⁹Xe gas exchange MRI with evaluatingthe cardiopulmonary dynamics of ¹²⁹Xe spectroscopy.

However, as recently as 2017, Bier et al., Proc. Intl. Soc. Mag. Reson.Med. 25 (2017) 2152, reported RBC chemical shifts that were notphysically possible given the in vitro RBC chemical shift values. Thatis, generally anything below 214.5 is considered not physicallypossible. For example, the 2017 work showed RBC frequencies as low as212 ppm. Embodiments of the present invention provide a robustacquisition and processing framework to provide clinically relevant RBCspectral parameters for dissolved phase ¹²⁹Xe with improvedquantification of spectral parameters. For example, the RBC chemicalshift in seven healthy volunteers changed from 213.8±0.5 to 217.6±0.6ppm and in IPF subjects it changed from 213.7±1.3 to 216.3±0.9 ppm usingthe improved processing methods and systems according to the presentinvention.

The inventors have found that to develop robust quantification methodsand algorithms, one must confront the challenges posed by the complexunderlying spectral structure of the ¹²⁹Xe-Barrier resonance and/or therelatively low spectral resolution dissolved phase ¹²⁹Xe signaloscillations. The inventors have also found that in addition to thevariations in RBC amplitude, there are other dynamic ¹²⁹Xe spectroscopicparameters (4-5 per resonance) that can be analyzed to provide insightsinto the underlying condition and/or distinguish between differentconditions.

Comparison of a healthy cohort or cohorts (i.e., a population norm) canbe used to provide insight into interpretations for patients withpulmonary vascular disease. Thus, embodiments of the present inventioncan provide: a) a strategy to acquire the temporal dynamics of ¹²⁹Xetransfer with sufficient temporal and spectral resolution allowing forclinically useful and/or statistically reliable results, b) a robustanalysis framework that quantifies dynamics such as cardiogenicoscillations, and c) representative data from healthy cohorts andpatients with disease in order to facilitate clinical interpretation.

The population norm can be established using one or more healthysubjects, i.e., humans, and may be provided based on age and gender orjust age or just gender.

Embodiments of the present invention successively acquire ¹²⁹Xe freeinduction decays (FIDs) about every 5-400 ms, more typically about every20 ms to about every 300 ms over a breathing maneuver to fullycharacterize the dynamics of each resonance (gas, barrier and RBC). Thisprovides “dynamic spectroscopy”, i.e., ¹²⁹Xe NMR signal parameters overa time period associated with a breathing maneuver that includes atleast one of inhale/breath-hold and exhale. Embodiments of the inventioncan then apply a complex time-domain curve fitting methodology and/oralgorithm that can robustly quantify each ¹²⁹Xe resonance (gas, barrierand RBC) by its amplitude, chemical shift, linewidth(s), and phase.

In some particular embodiments, a signal acquisition and processingalgorithm and/or methodology can be used that accommodates the lowersignal to noise (SNR) and spectral resolution of such dynamicallyacquired data in two ways. First, it can incorporate a tailored(defined) pre-processing step or steps to remove high-frequency noiseoutside of a physiologically plausible realm. Second, it can provide aninnovative treatment of the ¹²⁹Xe spectrum using curve fitting that ismodeled with one or more non-Lorentzian line shapes, preferablyrequiring no more than one or two additional fitting degree of freedom(relative to only Lorentzian) to preserve temporal and/or spectralresolution.

In some currently preferred embodiments, the barrier resonance lineshape is fit using a Voigt spectral profile, to incorporate its knowncomplexity, while requiring only one additional fitting degree offreedom. The terms “Voigt spectral profile” and “Voight line shape” areinterchangeably described herein as a “Voigt curve fitting function”.

Embodiments of the invention can generate spectral parameters sensitiveto gas exchange in the lung by acquiring the NMR raw signal data overthe course of a breathing maneuver that can include each ofinspiration/inhale, breath-hold, and exhalation/exhale.

FIG. 1 illustrates temporal changes in the spectroscopic parameters ofthe ¹²⁹Xe gas, barrier, and RBC resonances in a representative healthysubject during inhalation, breath hold (gray bar/medial part of plot),and exhalation. In this graph/plot, all amplitudes were normalized to amaxima/maximum ¹²⁹Xe barrier signal amplitude. For example, if themaximum barrier amplitude=10, and the maximum RBC amplitude=5, then theRBC graph would show a maximum signal of 0.5 while that of the barrierwould exhibit a maximum amplitude of 1. This can be performed by firstdetermining the value of the maximum barrier signal and then dividingthe gas, barrier, and RBC signal amplitudes by this value. By way ofanother example, the maximum raw barrier signal can be a constant valueof about 3.0×10³ and every amplitude can be divided by this constantvalue. Alternatively, the RBC amplitude can be divided by the barrieramplitude at each time point to generate a time-depended RBC:barrierratio, which is indicative of global gas exchange efficiency. The arrowsin FIG. 1 emphasize/point to some of the spectroscopic changes thataccompany the breathing maneuver and the line above the RBC amplitude(FIG. 1, FIG. 2 emphasizes/highlights the cardiogenic oscillations).

It is noted that other normalization factors may be used, such asnormalizing to a ¹²⁹Xe gas amplitude or a ¹²⁹Xe gas resonance signalvalue (i.e., a maximal, minimal, median or average gas amplitude) ornormalizing to any of these values for the barrier resonance.

Yet another way to normalize the amplitudes of the different spectralparameters can employ the barrier/gas phase with respect to time (i.e.,normalize on a time-point by time-point basis). This results in a plotof the RBC:barrier ratio or the RBC:gas ratio with respect to time.

FIG. 1 illustrates temporal changes in the spectroscopic parameters ofthe ¹²⁹Xe gas, barrier, and RBC resonances in a subject with IPF(subject 13) during inhalation, breath hold (gray bar), and exhalation.Again, all amplitudes are normalized to the maximum ¹²⁹Xe signal in thebarrier compartment. Unlike the healthy volunteer, the RBC resonanceexhibits notable oscillations at the heart rate not only in amplitudebut also in chemical shift and phase, as indicated by the black bar.

FIG. 2 illustrates normalized and detrended RBC spectral parameterdynamics during a breath hold from a representative healthy volunteerand two subjects with IPF, and two subjects with PAH and one subjectwith left heart failure (LHF). The solid line represents the sinusoidalfit. Note larger RBC amplitude oscillations in IPF, coupled with largerRBC frequency/phase oscillations. By contrast, the PAH patients exhibitsmaller RBC oscillations. The left heart (LHF) failure patient exhibitslarger RBC amplitude oscillations, but decreased and/or no significantfrequency (shift/ppm) and phase oscillations.

FIGS. 3A-4D illustrate peak-to-peak cardiogenic oscillations in RBCspectral parameters during the breath hold for healthy versus IPFsubjects. Oscillations in the RBC amplitude, chemical shift, and phaseare significantly larger for IPF subjects (red/broken line and on rightside of plots) than for healthy volunteers (P=0.008, P=0.001, andP=0.002). *Statistical difference between groups (P<0.05).

FIGS. 5A-5D compare oscillations in the RBC amplitude, chemical shift,and phase between the healthy (green and left side data of each plot),IPF (red and middle of each plot) and PAH (magenta and right side dataof each plot) cohort. IPF is distinguished by RBC amplitude, frequencyand phase oscillations that are significantly larger than in the normalcohort. PAH is distinguished by RBC amplitude oscillations that aresignificantly smaller than in the normal cohort.

FIG. 6A is a set of dissolved phase fits for a large average of FIDsthat exhibit minimal residual error for both 3-Lorentizan fits (leftside plots) and barrier Voigt model fits (right side panels). FIG. 6B isa set of plots of dynamically acquired spectroscopy for a healthyvolunteer that returns ill-condition fits for the barrier resonances inthe 3-Lorentzian model (left and middle panels), but which is overcomeby the barrier Voigt model (right side panels). The FWHM (ppm) panel ofthe barrier using the Voigt model has a FWHM_(G) line and a Lorentzianline (the Lorentzian shown in solid line above the FWHM_(G) line) whichprovides a more reliable RBC fit (FIGS. 1 and 2, for example).

In the past, Robertson et al proposed to manage the complexity of thebarrier resonance by using two Lorentzian resonances rather than one.See, Robertson et al., Uncovering a third dissolved-phase ¹²⁹Xeresonance in the human lung: Quantifying spectroscopic features inhealthy subjects and patients with idiopathic pulmonary fibrosis.Magnetic resonance in medicine 2017; 78(4):1306-1315, the contents ofwhich are hereby incorporated by reference as if recited in full herein.However, this approach yields poorly conditioned fits of dynamicspectroscopy because it requires more fitting degrees of freedom. TheVoigt profile has a line shape that represents the convolution of aLorentzian peak with a Gaussian distribution and requires only oneadditional fitting degree of freedom. Specifically, it returns twodistinct linewidth parameters—a Lorentzian and a Gaussian parameter.See, Marshall et al., Use of Voigt lineshape for quantification of invivo ¹H spectra, Magnetic resonance in medicine 1997; 37(5):651-657, thecontents of which are hereby incorporated by reference as if recited infull herein.

In other embodiments, other curve fitting functions that providesufficient temporal and spectral resolution to yield accurate barrierresonance data can be used, i.e., the ¹²⁹Xe spectrum can be modeled withone or more non-Lorentzian line shapes or a mixture of one or morenon-Lorentzian and Lorentzian line shapes.

FIG. 7A is a set of color-coded images (ventilation, barrier:gas,RBC:gas) of a COPD patient with severe ventilation defects, but barrieruptake and RBC uptake are relatively well-matched. FIG. 7B is a set ofcorresponding color-coded images of a COPD patient in whom RBC transferdefects are disproportionately worse than the barrier uptake, suggestingpossible pre-capillary pulmonary hypertension.

FIG. 8A is an example flow chart of signal processing actions that canbe used to generate the dynamic spectral parameters according toembodiments of the present invention. Data at a range of frequencies isobtained. The data includes dissolved and gas phase ¹²⁹Xe resonances(gas, barrier and RBC resonances) to obtain an entire range for curvefitting and determining frequency/chemical shift of each resonance overa time period associated with a breathing maneuver comprising one ormore of inhalation, breath hold and exhalation. (block 100). FreeInduction Decays (FIDs) of the obtained NMR signal over the time periodare curve fit to a function that models the RBC and gas peaks asLorenztian curves with an amplitude, frequency, FWHM, and phase, and thebarrier resonances as a Voigt profile with an additional Gaussian FWHM(block 110). That is, the ¹²⁹Xe barrier resonance can be modeled (orfit) using a Voigt line shape and the ¹²⁹Xe-RBC and ¹²⁹Xe-gas phaseresonances can be modeled (fit) using (only) a respective Lorentzianline shape. The barrier resonance has only one frequency and fitting itto a Voigt function allows it to have concurrent Lorentzian and GaussianFWHMs, but only one amplitude, frequency and phase. No independentLorentzian and Gaussian curves are required; the barrier signal issimply fit to a single line shape that has two linewidth parameters.This accommodates the complexity of the barrier line shape whilelimiting the additional required fitting degrees of freedom. The curvefitting can be carried out to identify barrier versus RBC versus gassignal in a manner that minimizes error between the model functions andthe data.

¹²⁹Xe gas, barrier and RBC spectral parameters are generated based onthe curve fit: the gas, barrier and RBC spectral parameters each includeamplitude, chemical shift (ppm), FWHM (ppm) and phase (degrees) and thebarrier spectral parameter further includes a FWHM_(G) over the timeperiod (block 120).

An estimate of amplitude, frequency, FWHM and phase with at leastfrequency and FWHM based on a median or average of one or more healthysubjects can be provided and used as initial inputs for the curvefitting (block 102).

The FIDs can comprise an average of a selected subset of raw datadynamic FIDs averaged together at corresponding different time points tocreate a first high SNR FID for an initial curve fit (block 112). Forexample, 3-10 FIDs, such as 3, 4, 5, 6, 7, 8, 9 or 10 FIDs averagedtogether at corresponding time points during a breathing maneuver toimprove SNR.

Amplitudes can be normalized to a (maximum) barrier amplitude and/or gasamplitude ¹²⁹Xe signal (block 122).

A ¹²⁹Xe gas phase frequency can be defined as a 0 ppm referencefrequency (block 114).

The resonance frequencies can be converted to chemical shifts (ppm)units by using the gas phase frequency as a reference frequency andconvert the FWHM from hertz to ppm using the ¹²⁹Xe Larmor frequency or acenter frequency of ¹²⁹Xe for the MRI scanner (block 115). For example,if the scanner transmitter frequency is 34 MHz and gas-phase signal isdetected at 0 Hz, while RBC signal is detected at 7.378 kHz, the RBCchemical shift is 7.378 kHz/34 MHz or 217 ppm.

The curve fit results can be electronically evaluated to determinewhether an RBC chemical shift is ≥214.5 ppm and a barrier chemical shiftis ≥196.0 ppm (block 116). If this condition is not met, then theoriginal estimates or inputs can be updated and/or a larger number ofFIDs can be used to provide the averaged FID for a revised first highSNR FID, then a second curve fit can be performed (block 117). If yes,the curve fitting is acceptable and no iterative change or further curvefitting or adjustment is required. If no, initial estimates can beupdated/revised. Also, RBC frequency can be evaluated to confirm it isin a range of 215-220 ppm, and the barrier frequency can be evaluated toconfirm it is in a range of 195-198 ppm, and FWHMs can be evaluated toconfirm they are less than 20 (block 118).

The frequency (chemical shift) of the gas phase reference can also beelectronically evaluated for accuracy to make sure it is notartificially identified based on a bad fit due to poor signalacquisition and/or low SNR (block 119).

A cardiopulmonary or pulmonary disease state or condition can beidentified based on correlated disease signature patterns associatedwith the dynamic ¹²⁹Xe spectroscopic parameters (block 124).

A likelihood of a presence or absence of PAH, LHF, IPF can be identifiedbased on the signature patterns that include no significant, increasedor decreased oscillations and/or statistically validated peak-peakvariation relative to a population norm (normal cohort) in one or moreof: amplitude oscillations, phase oscillations, FWHM(s) oscillations andchemical shift oscillations (ppm) in one or more of the RBC, gas andbarrier spectral parameters (block 126).

Amplitudes of spectral parameters associated with a breath-hold timeperiod of between 1-30 seconds can be normalized and detrended, thenoptionally a sinusoidal fit can be applied to at least some of the RBCspectral parameters (block 128).

A disease state or condition can be identified based at least in part onthe shape of the RBC amplitude oscillations (block 129). Embodiments ofthe present application contemplate that the actual shape of the RBCoscillations can reveal information of an underlying disease state orcondition. The RBC oscillations are not (always) purely sinusoidal andthe way the oscillations rise and fall can provide information about theunderlying disease condition.

Time-dependent amplitudes can be detrended over a breath-hold period toflatten the amplitude signal to account for signal decay and increasesignal oscillation relative to a non-detrended amplitude signal (block130). That is, the RBC spectral parameters can be normalized anddetrended or detrended and normalized. The breath hold time period canbe between 1-30 seconds. Optionally, a sinusoidal fit can be applied toat least some of the (adjusted) RBC spectral parameters.

FIG. 8B is another example flow chart according to embodiments of thepresent invention. Raw data is read in (obtained) (block 150). A SIFTtechnique can be applied for noise reduction (block 155). See, Doyle etal., SIFT, a postprocessing method that increases the signal-to-noiseratio of spectra which vary in time, Journal of Magnetic Resonance,Series B. 1994; 103(2):128-133; and Rowland et al., AP, Spectralimprovement by fourier thresholding of in vivo dynamic spectroscopydata. Magnetic resonance in medicine. 2015, the contents of which arehereby incorporated by reference as if recited in full herein.

Optionally, the middle third of FIDs of the raw data can be averagedtogether to create a high SNR FID (block 160). Initial estimates(guesses) for amplitude, frequency, FWHM, FWHM_(G), and phase areprovided/defined (block 163). Initial guess/estimates for a high-SNR FIDcan be provided as a first curve fit iteration and the outcome of thatthat fit used to provide updated guesses for smaller blocks of averagesthat contain the dynamics.

Frequency and FWHM and FWHM_(G) estimates can be based on an average (ormedian) value of a healthy cohort (block 163). The high SNR FID can befit using a barrier Voigt model (block 165). The gas phase frequency canbe defined as the 0 ppm reference frequency (block 167). The results ofthe high SNR fit can be converted to ppm units (block 170).

The RBC chemical shift can be evaluated to confirm it is ≥214.5 ppm andthe barrier chemical shift can be evaluated to confirm it is ≥196.0 ppm(block 172). If these conditions are not met (false), the fitting canstop (block 174). For example, a stop decision can be made based on anumber of tries or a defined SNR threshold. If true, the initialestimates/guesses can be updated using the results from a higher SNRfitting and/or a higher SNR FID (block 175). The high or a higher SNRFID can be fit with the updated guesses/estimates (block 180). Each timepoint of the high SNR FID can have 5 FIDs averaged together (block 182).While 5 FIDs are believed to provide sufficient resolution, fewer FIDscan be averaged together, such as 3 or 4 FIDs, or more than 5, such as arange of 6-10, for certain embodiments.

FIG. 8C is another flow chart of actions that can be used to evaluate asubject according to embodiments of the present invention. A database ofdisease signature patterns of oscillations of gas, barrier and RBC 129Xeresonances is provided (block 200).

Raw (FIDs) of NMR signal of hyperpolarized ¹²⁹Xe of a subject during abreathing maneuver comprising one or more on inhale, breath-hold andexhale are obtained (block 210).

Graphs of oscillations associated with ¹²⁹Xe barrier, RBC and gasresonances are generated (block 220).

The subject can be identified as having pre or post capillary pulmonaryvasculature disease based on oscillation the oscillations of RBCchemical shift and RBC amplitude (block 230). For example, only patientswith pure pre-capillary disease benefit from PH medication while thosewith any post-capillary obstruction are contradicted from treatmentusing PH medication so proper characterization is important.

The database can also include a disease threshold of RBC:Barrier ratiowhich is reduced in IPF subjects relative to a population norm (block202).

The FIDs or the averaged FID can be pre-processed to filter non-dominantfrequencies (i.e., frequencies associated with noise) out of an indirecttime dimension to smooth temporal changes between FIDs while leaving aspectral-frequency domain intact (block 212).

The FIDs or the averaged FID can be complex fitted in a time domain(block 214).

A model in which the RBC and gas peaks are Lorentzians with anamplitude, chemical shift, FWHM and phase and the barrier peak is aVoight profile with an additional Gaussian linewidth (FWHM_(G)) for thebarrier resonance (block 215).

The curve fitting can be carried out using the equation S_(fit), below(block 216).

$\begin{matrix}{s_{fit} = {{a_{rbc}e^{{i\; \phi_{r\; {bc}}} + {2\; \pi \; {if}_{rbc}t}}e^{{- \pi}\; t \times {FWHM}_{rbc}}} + {a_{bar}e^{{i\; \phi_{bar}} + {2\; \pi \; {if}_{bar}t}}e^{{- \pi}\; t \times {FWHM}_{bar}}e^{{- 4}\; l\; n\; 2 \times t^{2}{FWHM}_{G_{bar}^{2}}}} + {a_{gas}e^{{i\; \phi_{gas}} + {2\; \pi \; i\; f_{gas}t}}e^{{- \pi}\; t\; \times {FWHM}_{gas}}}}} & {{EQN}(1)}\end{matrix}$

Temporal variations in ¹²⁹Xe RBC resonance occurring at the cardiacfrequency (about 1 Hz) can be extracted (block 211).

Amplitude of an RBC peak can be corrected using T1app (block 217).

T1app can be calculated by fitting RBC amplitude within the breath-holdperiod to Ae^(−t/T1) ^(app) (block 218).

Stated differently, the amplitude “A” of the RBC signal can be correctedby dividing the signal by exp(−t/T1_(app))*exp(−t_(start)/T1_(app)),where the second term is a scaling term to adjust the amplitude to matchwith the raw signal. The signal amplitude is in arbitrary units.

The RBC amplitude can be calculated as a percent change from baseline(block 222). For example, the RBC signal during the breath hold can befit to the function of block 216. Then the value of the function at eachtime point, t, can be calculated and used as the baseline. The RBCbaseline can be viewed as a percent change by taking the differencebetween the measured value and the calculated value and dividing by thecalculated value. Baseline can be defined as the result of theexponential decay fitting in block 218 and is essentially a percentagechange from a large average over many oscillations:

(RBC_signal−RBC_fitted)/RBC_fitted  EQN 2

The action at block 222 can use the corrected amplitude from block 217.

The obtained signal can include pre and post drug challenge or drugdelivery data (block 210).

¹²⁹Xe MRI images of gas exchange can be evaluated with the oscillationgraphs to identify a disease state or monitor progression (block 232).

The oscillation frequency can be used to determine a subject's heartrate.

Static values of one or more of the spectral parameters can also beevaluated to obtain information regarding different disease statesand/or conditions, alone or in combination with one or more of thedynamic spectral parameters.

FIG. 8D is a flow chart of actions that can be used to adjust amplitudeof RBC oscillations which may be important to interpreting RBC amplitudeoscillations. RBC amplitude oscillations of a subject are obtained(block 300). The obtained RBC oscillations can be adjusted for cardiacstroke volume and a new parameter referred to as “pulmonary exchangevolume” (block 310).

Stroke volume is the volume of blood the right side of the heart pumpsout with each beat. A nominal (human adult) value is commonly reportedas 94 or 95 ml. All things being equal, a larger cardiac stroke volumeis likely to generate larger RBC amplitude oscillations. Stroke volumecan be determined invasively from right heart catheterization, measuredby ventricle volumes from an echocardiogram, or determinednon-invasively from a certain type of time-resolved proton cardiac MRIacquisition. See, Alfakih, Khaled, et al. “Normal human left and rightventricular dimensions for MRI as assessed by turbo gradient echo andsteady-state free precession imaging sequences.” Journal of MagneticResonance Imaging 17.3 (2003): 323-329. Absent such data, it may beestimated from alometric scaling principles. See, de Simone, Giovanni,et al. “Stroke volume and cardiac output in normotensive children andadults: assessment of relations with body size and impact ofoverweight.” Circulation 95.7 (1997): 1837-1843. The contents of thesearticles are hereby incorporated by reference as if recited in fullherein.

Information from the shape of the RBC oscillation amplitude can be usedto potentially help differentiate pure pre-capillary disease frompost-capillary disease versus combined post- and pre-capillary pulmonaryhypertension (Cpc-PH).

“Pulmonary exchange volume” is a measure of the lung volume receivingblood from the stroke volume. For a given stroke volume, a largerpulmonary exchange volume will attenuate the RBC amplitude oscillations.

Pulmonary exchange volume (“PEV”) can be derived from ¹²⁹Xe gas exchangeMRI. It can be modeled as a thoracic cavity volume minus the volume thatconsists of ventilation defects, minus the volume that doesn'tparticipate in RBC transfer.

Mathematically:

PEV=TCV*(1−VDP−RDP),  EQN 3

where TCV=thoracic cavity volume, VDP=ventilation defect percentage, andRDP=RBC transfer defect percentage. VDP and RDP can be calculated fromthe gas exchange ¹²⁹Xe MRI images (see, FIGS. 7A, 7B). (block 315)

For example, a subject with 4 liter thoracic cavity, with 10% VDP+10%RDP has 80%×4 liter=3.2 liters of pulmonary exchanging volume.

Embodiments of the invention contemplate that the dynamic spectroscopicRBC amplitude oscillations can be multiplied by a pulmonary exchangevolume and divided by cardiac stroke volume.

Cardiac stroke volume can also be measured by ventricle volumes from anechocardiogram. Alternatively, published normative values of 94 or 95 mLor other defined normative values based on allometric scaling can beused. For example, stroke volume is calculated by dividing cardiacoutput by heart rate. Cardiac output scales with body mass to the powerof ¾, while heart rate scales to the power of −¼. Thus, stroke volume isexpected to scale linearly with body mass.

A larger blood volume will naturally diminish RBC amplitudeoscillations, whereas a larger cardiac stroke volume would enhance theRBC amplitude oscillations. This suggests that in patients with IPF, whooften have a very small restricted thoracic cavity, enhanced RBCoscillations are likely a natural consequence of reduced exchangeableblood volume.

The “adjusted” RBC amplitude oscillations can multiply the obtained(i.e., originally measured) RBC amplitude oscillations A_(RBC) by:

(V_stroke_ref/V_stroke)*(PEV/PEV_ref).  EQN 4

where V_stroke_ref is a reference stroke volume like 94 ml or 95 ml(adult), V_stroke is the patient's actual stroke volume, PEV_ref is areference exchange volume, and PEV is the patient's measured exchangevolume (block 320).

Referring again to FIG. 3, for example, a subject can be identified ashaving IPF which is characterized by RBC amplitude oscillations that aresignificantly larger (i.e., about 1.5-2× larger) than in healthyvolunteers. In IPF patients, the RBC frequency (chemical shift/ppm) andphase oscillations are also significantly larger than in the healthycohort, typically at least 2×, 3×, 4× or 5× above a healthy cohort. Inthe IPF versus healthy cohort, RBC amplitude variations were nearlytwice as high (16.8±5.2% vs 9.7±2.9%; P=0.008), chemical shiftoscillations were more than 5-fold higher (0.43±0.33 ppm vs 0.083±0.05ppm; P<0.001), and RBC phase oscillations were more than 5-fold higher(7.7±5.6° vs 1.4±0.8°; P<0.001).

In IPF, the RBC amplitude oscillations are thought to be large becausethe pulmonary exchange volume, PEV, is so small. It is contemplated thatwhen RBC oscillations are corrected for PEV, they will potentiallysignificantly decrease. Thus, more specific diagnostic features ofdynamic spectroscopy in patients with IPF are the chemical shift andphase oscillations, which do not require correction for PEV. To date,such oscillations have only been seen in patients with IPF.

It is contemplated that the larger RBC amplitude oscillations are eitherthe result of post-capillary obstruction caused by fibrosis, or cardiacoutput being delivered to a significantly smaller capillary bloodvolume. Importantly, the RBC frequency and phase oscillations areexpected to be caused by delayed oxygenation associated withinterstitial lung disease. This is uniquely detectable by virtue of thesensitivity of the ¹²⁹Xe-RBC resonance to blood oxygenation. Theobservation that this frequency oscillates in the IPF cohort is ameasure of interstitial thickening that causes delayed diffusion ofoxygen.

The PAH cohort can be characterized as exhibiting RBC oscillations thatare significantly smaller than the normal cohort (FIG. 3). Moreover,Group 1 PH does not exhibit RBC chemical shift or phase oscillationsthat are significantly different from normal.

These findings are particularly noteworthy in the small population usedto generate the dynamic spectroscopy parameters for patients with thenoted conditions (i.e., IPF, PAH and LHF) because these patients are onmedication and are relatively well-controlled compared to patients whowould present for diagnosis.

Although not wishing to be bound by any particular theory, the smallerRBC amplitude oscillations are explained by higher impedance in thepulmonary arteries and arterioles, which serves to attenuate the changesin capillary blood volume that occur at diastole.

PH can exhibit large RBC amplitude oscillations, but with little or noRBC frequency/phase oscillations. The enhanced RBC amplitudeoscillations are thought to be a marker of post-capillary obstruction.

RBC frequency/phase oscillations appear to be uniquely associated withdelayed oxygenation that occurs in interstitial lung disease,particularly IPF.

It is not yet known if the RBC frequency/phase oscillations areassociated with non-specific interstitial pneumonia, but it iscontemplated that this form of pneumonia can be differentiated from IPFbased on the ¹²⁹Xe spectral parameters, dynamic, static or dynamic andstatic ¹²⁹Xe spectral parameters relative to a patient population and“healthy cohort” or population norm.

In some particular embodiments, it is contemplated that the defineddifferent disease patterns can distinguish post-capillary vasculardisease from pre-capillary vascular disease by variations above or belowa healthy cohort or population norm.

Embodiments of the invention can use decreased peak to peak RBCamplitude oscillations relative to a defined norm to indicate PAH.

Embodiments of the invention can evaluation the shape of the RBCamplitude oscillations to indicate a combined pre- and post-capillaryvascular disease state.

Diminished RBC amplitude oscillations appear to be a unique signature ofpre-capillary, arterial disease, and patients exhibiting these maybenefit from PAH medications.

Enhanced RBC amplitude oscillations are likely a signature ofpost-capillary disease and these patients would be harmed by receivingPAH medications.

It is contemplated that there are several potential ways to acquiredynamic spectroscopy data that improve upon standard acquisition.

Embodiments of the invention may be able to detect potentially treatablepre-capillary PH in patients who have existing lung disease (like COPD,IPF, etc. . . . ) based on gas exchange MRI (i.e., FIGS. 7A, 7B). Thatis, patients with impaired RBC transfer that affects adisproportionately larger percentage of the lung than can be explainedby poor barrier condition (low barrier in COPD, or high barrier in IPF)and gas exchange ¹²⁹Xe MRI can be used to identify additional featurecharacteristics.

Embodiments of the invention can acquire gas exchange MRI and/or dynamicspectroscopy before and after administration of a pharmaceutical agent,such as a vasodilator, hyperoxia, diuretic or prostacyclins. Comparisonof changes in oscillations in the spectral parameters of ¹²⁹Xe dynamicspectroscopy, for example, can be detected to determine impact of theagent on function. For example, delivery of inhaled nitric oxide orinhaled prostacyclins may be able to reveal areas in gas exchange imagesof the lung that are susceptible to vasodilation which would showrestored RBC transfer. Similarly, dynamic spectroscopy can showenhanced/increased RBC oscillation amplitudes relative to prior to suchadministration.

A hyperoxia challenge may also reveal similar improvements in restoringregional RBC transfer and RBC oscillation amplitudes.

In some COPD patients, massively diminished RBC amplitude oscillationsare present even after correcting for the relatively large exchangeablecapillary blood volumes. This could indicate pre-capillary pulmonaryhypertension.

Turning now to FIG. 9, an example medical system 1100 is shown. Themedical system 1100 can comprise at least one server 1150. The at leastone server 1150 can be configured with a dynamic ¹²⁹Xe spectroscopyanalysis module 1124 and/or be configured with a database of ¹²⁹Xedisease signature patterns 1126.

The at least one server 1150 can communicate with an imaging site 1110and/or a clinician site 1210, typically via at least one respectivedigital processor 1110 p, 1210 p. The imaging site 1110 can be ahospital or other facility (mobile or permanent) with an MRI Scanner1125. The clinician site 1210 can be remote from or at the imaging site1110. The server 1150 can be remote from both the imaging site 1110 andthe clinician site 1210. Alternatively, the server 1150 can be onsiteeither the clinician or imaging site 1210, 1110, respectively.

The server 1150 can be integrated into a single server or may bedistributed into one or more servers or other circuits or databases at asingle physical site or at spatially separate locations. Similarly, thedynamic ¹²⁹Xe spectroscopy analysis module 1124 held by the one or moreservers 1150 can be distributed into multiple processors or databases orintegrated into one. The ¹²⁹Xe dynamic spectra can be electronicallytransmitted using a DICOM system to the 1150 server for the automatedimage analysis.

The server 1150 may be embodied as a standalone server or may becontained as part of other computing infrastructures. The server 1150may be embodied as one or more enterprise, application, personal,pervasive and/or embedded computer systems that may be standalone orinterconnected by a public and/or private, real and/or virtual, wiredand/or wireless network including the Internet, and may include varioustypes of tangible, non-transitory computer-readable media. The server1150 may also communicate with a computer network via wired or wirelessconnections, and may include various types of tangible, non-transitorycomputer-readable media.

The server 1150 can be provided using cloud computing which includes theprovision of computational resources on demand via a computer networkwith appropriate firewalls 1160 and privacy protocols to comply withHIPPA or other regulatory requirements. The resources can be embodied asvarious infrastructure services (e.g., compute, storage, etc.) as wellas applications, databases, file services, email, etc. In thetraditional model of computing, both data and software are typicallyfully contained on the user's computer; in cloud computing, the user'scomputer may contain little software or data (perhaps an operatingsystem and/or web browser), and may serve as little more than a displayterminal for processes occurring on a network of external computers. Acloud computing service (or an aggregation of multiple cloud resources)may be generally referred to as the “Cloud”. Cloud storage may include amodel of networked computer data storage where data is stored onmultiple virtual servers, rather than being hosted on one or morededicated servers.

A plurality of the imaging sites 1110 can be in communication with theserver 1150 and one or more clinician sites 1210. The server 1150 canreceive and analyze NMR data of respective patients from different sites1110 at any one time. It is contemplated that the server 1150 cananalyze and generate patient reports in a FIFO (first in first out)manner, optionally with rush or ranked priority reviews. Multipleanalyses can be performed concurrently or serially at the server 1150 orother devices in communication with the server 1150 and associatedreports can be generated and transmitted to one or more devices ofclinician users 1211.

An imaging site 1110 and/or a clinician site 1210 can communicate withthe server 1150 via a computer network, such as one or more of localarea networks (LAN), wide area networks (WAN) and can include a privateintranet and/or the public Internet (also known as the World Wide Web or“the web” or “the Internet.”

The server 1150 can be configured to send analysis reports orsubject-test or evaluation data to one or more clinician devices 1211such as computers, tablets or smartphones (shown as at the imaging sitebut one or more may be remote from the imaging site).

FIG. 10 is a schematic diagram of an MRI scanner 1125 with asuperconducting magnet 1140, a gradient system 1165 and an RF coil 1170that communicates with an RF amplifier (not shown) associated with theMRI scanner as is well known to those of skill in the art. Signal fromthe RF coil 1170 may be transmitted to the receiver 1205 via a cable(typically a BNC cable). The MRI scanner 1125 also includes a controller1105, a frequency adjustor circuit 1102 that can tune the MRI scanner togenerate a desired RF excitation frequency for exciting hyperpolarizeddissolved phase ¹²⁹Xe, and a display 1130. The display 1130 may be localor remote and may be provided as part of a clinician workstation. Thedisplay 1130 can be configured to display the RBC and barrier imagessubstantially concurrently with plots of oscillation of ¹²⁹Xe to provideclinical data of the gas-exchange regions of the lung.

The MRI scanner 1125 can also include or be in communication with aDynamic Spectroscopy module 1224, which can programmatically communicatewith the frequency adjustor circuit 1102 and receiver 1205 toelectronically (automatically) switch operational modes, frequencies,phases and/or electronically direct the excitation and acquisition ofappropriate signals, and generate the cardiopulmonary spectroscopicparameters according to some embodiments of the invention.Alternatively, the NMR signal data of respective subjects can becollected and transmitted to the server 1150 for post-acquisitionprocessing. The NMR signal data can be transmitted from a PACS (picturearchiving and communication system) 1224 to the server 1150.

Referring now to FIG. 11, a data processing system 1316 is shown thatmay be used to provide the ¹²⁹Xe dynamic spectroscopy module 1124 (whichcan provide dissolved phase ¹²⁹Xe of gas exchange for NMR signaldecomposition), and a curve fit module 1327. Thus, in accordance withsome embodiments of the present invention, the system 1316 comprises amemory 1336 that communicate with a processor 1300. The data processingsystem 1316 may further include an input/output (I/O) circuits and/ordata port(s) 1346 that also communicate with the processor 1300. Thesystem 1316 may include removable and/or fixed media, such as floppydisks, ZIP drives, hard disks, or the like, as well as virtual storage,such as a RAMDISK. The I/O data port(s) 1346 may be used to transferinformation between the data processing system 1316 and another computersystem or a network (e.g., the Internet). These components may beconventional components, such as those used in many conventionalcomputing devices, and their functionality, with respect to conventionaloperations, is generally known to those skilled in the art.

FIG. 11 illustrates a processor 1300 and memory 1336 that may be used inembodiments of systems in accordance with some embodiments of thepresent invention. The processor 1300 communicates with the memory 1336via an address/data bus 1348. The processor 1300 may be, for example, acommercially available or custom microprocessor. The memory 1336 isrepresentative of the one or more memory devices containing the softwareand data used for providing ¹²⁹Xe MRI image data or ¹²⁹Xe NMR spectradata in accordance with some embodiments of the present invention. Thememory 1336 may include, but is not limited to, the following types ofdevices: cache, ROM, PROM, EPROM, EEPROM, flash, SRAM, and DRAM.

As shown in FIG. 11, the memory 1336 may contain up to two or morecategories of software and/or data: an operating system 1352, I/O DeviceDrivers 1358, data 1356 and application programs 1354. FIG. 11illustrates that the data 1356 can include patient NMR spectra data1326.

As will be appreciated by those of skill in the art, the operatingsystem 1352 may be any operating system suitable for use with a dataprocessing system, such as IBM®, OS/2®, AIX® or zOS® operating systemsor Microsoft® Windows-based operating systems (e.g., Windows XP, WindowsNT, Windows 10, Windows Server 2016) or Unix or Linux™ IBM, OS/2, AIXand zOS are trademarks of International Business Machines Corporation inthe United States, other countries, or both while Linux is a trademarkof Linus Torvalds in the United States, other countries, or both.Microsoft and Windows are trademarks of Microsoft Corporation in theUnited States, other countries, or both. Virtualized platformssupporting one or more operating systems may also be used (i.e.,VMWARE). The input/output device drivers 1358 typically include softwareroutines accessed through the operating system 1352 by the applicationprograms 1354 to communicate with devices such as the input/outputcircuits 1346 and certain memory 1336 components. The applicationprograms 1354 are illustrative of the programs that implement thevarious features of the circuits and modules according to someembodiments of the present invention. Finally, the data 1356 representsthe static and dynamic data used by the application programs 1354 theoperating system 1352 the input/output device drivers 1358 and othersoftware programs that may reside in the memory 1336.

While the present invention is illustrated in FIG. 11 with reference tothe application programs 1354 with Modules 1124 and 1327, as will beappreciated by those of skill in the art, other configurations fallwithin the scope of the present invention. For example, rather thanbeing application programs 1354 these circuits and modules may also beincorporated into the operating system 1352 or other such logicaldivision of the data processing system. Furthermore, while theapplication program(s) 1354 is illustrated in a single data processingsystem, as will be appreciated by those of skill in the art, suchfunctionality may be distributed across one or more data processingsystems in, for example, the type of client/server arrangement describedabove. Thus, the present invention should not be construed as limited tothe configurations illustrated but may be provided by other arrangementsand/or divisions of functions between data processing systems. Forexample, although FIG. 11 is illustrated as having various modules, oneor more of these modules may be combined or separated without departingfrom the scope of the present invention.

Although FIG. 11 illustrates exemplary hardware/software architecturesthat may be used, it will be understood that the present invention isnot limited to such a configuration but is intended to encompass anyconfiguration capable of carrying out operations described herein.Moreover, the functionality of the data processing systems and thehardware/software architectures may be implemented as a single processorsystem, a multi-processor system, or even a network of stand-alonecomputer systems, in accordance with various embodiments of the presentinvention.

Computer program code for carrying out operations of data processingsystems discussed above with respect to the figures may be written in ahigh-level programming language, such as PYTHON, Java, C, and/or C++,for development convenience. In addition, computer program code forcarrying out operations of embodiments of the present invention may alsobe written in other programming languages, such as, but not limited to,interpreted languages. Some modules or routines may be written inassembly language or even micro-code to enhance performance and/ormemory usage. It will be further appreciated that the functionality ofany or all of the program modules may also be implemented using discretehardware components, one or more application specific integratedcircuits (ASICs), or a programmed digital signal processor ormicrocontroller.

The present invention is described herein with reference to flowchartand/or block diagram illustrations of methods, systems, and computerprogram products in accordance with exemplary embodiments of theinvention. These flowchart and/or block diagrams further illustrateexemplary operations for administering and/or providing calendar-basedtime limited passcodes, in accordance with some embodiments of thepresent invention. It will be understood that each block of theflowchart and/or block diagram illustrations, and combinations of blocksin the flowchart and/or block diagram illustrations, may be implementedby computer program instructions and/or hardware operations. Thesecomputer program instructions may be provided to a processor of ageneral purpose computer, a special purpose computer, or otherprogrammable data processing apparatus to produce a machine, such thatthe instructions, which execute via the processor of the computer orother programmable data processing apparatus, create means and/orcircuits for implementing the functions specified in the flowchartand/or block diagram block or blocks.

These computer program instructions may also be stored in a computerusable or computer-readable non-transient memory that may direct acomputer or other programmable data processing apparatus to function ina particular manner, such that the instructions stored in the computerusable or computer-readable memory produce an article of manufactureincluding instructions that implement the function specified in theflowchart and/or block diagram block or blocks.

The computer program instructions may also be loaded onto a computer orother programmable data processing apparatus to cause a series ofoperational steps to be performed on the computer or other programmableapparatus to produce a computer implemented process such that theinstructions that execute on the computer or other programmableapparatus provide steps for implementing the functions specified in theflowchart and/or block diagram block or blocks.

The flowcharts and block diagrams illustrate the architecture,functionality, and operations of some embodiments of methods, systems,and computer program products. In this regard, each block represents amodule, segment, or portion of code, which comprises one or moreexecutable instructions for implementing the specified logicalfunction(s). It should also be noted that in other implementations, thefunction(s) noted in the blocks might occur out of the order noted. Forexample, two blocks shown in succession may, in fact, be executedsubstantially concurrently or the blocks may sometimes be executed inthe reverse order, depending on the functionality involved.

The present invention may be embodied as systems, methods, and/orcomputer program products. Accordingly, the present invention may beembodied in hardware and/or in software (including firmware, residentsoftware, micro-code, etc.). Furthermore, the present invention may takethe form of a computer program product on a computer-usable orcomputer-readable storage medium having computer-usable orcomputer-readable program code embodied in the medium for use by or inconnection with an instruction execution system. In the context of thisdocument, a computer-usable or computer-readable medium may be anynon-transient medium that can contain, store, communicate, propagate, ortransport the program for use by or in connection with the instructionexecution system, apparatus, or device.

The computer-usable or computer-readable medium may be, for example, anelectronic, magnetic, optical, electromagnetic, infrared, orsemiconductor system, apparatus, device, or propagation medium. Morespecific examples (a non-exhaustive list) of the computer-readablemedium would include the following: an electrical connection having oneor more wires, a portable computer diskette, a random access memory(RAM), a read-only memory (ROM), an erasable programmable read-onlymemory (EPROM or Flash memory), an optical fiber, and a portable compactdisc read-only memory (CD-ROM).

Furthermore, the user's computer, a remote computer (i.e., server) orboth, may be integrated into or communicate with other systems, such ascontrol cabinets of MRI scanner systems, hospital PACS (picturearchiving and communication system) and/or clinician workstations, forexample.

Non-Limiting Examples will be discussed below.

EXAMPLES Example 1 Subject Recruitment

This study was approved by the Duke University Institutional ReviewBoard, and written informed consent was provided by all subjects priorto participation. Dynamic ¹²⁹Xe spectra were acquired in 8 healthyvolunteers (7 males and 1 female; 26.4±4.9 years old) and 9 subjectswith IPF (7 males and 2 females; 66.1±5.6 years old). Healthy volunteershad no known pulmonary disorders, no cardiac arrhythmias, and no historyof smoking. Subjects with IPF were diagnosed according to ATS criteria,confirming a UIP pattern on CT or from surgical lung biopsy. See Raghuet al. An official ATS/ERS/JRS/ALAT statement: idiopathic pulmonaryfibrosis: evidence-based guidelines for diagnosis and management.American journal of respiratory and critical care medicine. 2011;183(6):788-824.

Xenon Polarization and Delivery

Using a commercially available polarizer (Model 9810, Polarean, Inc,Durham, N.C., USA), 300 mL of isotopically enriched ¹²⁹Xe (85%) washyperpolarized to approximately 20% via rubidium vapor spin-exchangeoptical pumping. Hyperpolarized ¹²⁹Xe was cryogenically accumulated andthawed into 1 L Tedlar bag (Jensen Inert Products, Coral Springs, Fla.).This provided a 51-mL dose equivalent (the product of polarization,enrichment and xenon volume) of hyperpolarized ¹²⁹Xe. See He et al. Doseand pulse sequence considerations for hyperpolarized ¹²⁹Xe ventilationMRI. Magnetic resonance imaging. 2015; 33(7):877-885; the contents ofwhich is hereby incorporated by reference as if recited in full herein.The bag volume was expanded to 1 L using ultra-high-purity N₂.

After two preparatory breaths, subjects inhaled ¹²⁹Xe from functionalresidual capacity (FRC), then held their breath for 8 seconds, and thenslowly exhaled. See Kaushik et al. Measuring diffusion limitation with aperfusion-limited gas-hyperpolarized ¹²⁹Xe gas-transfer spectroscopy inpatients with idiopathic pulmonary fibrosis. Journal of AppliedPhysiology. 2014; 117(6):577-585; the contents of which is herebyincorporated by reference as if recited in full herein. Data acquisitionbegan during inhalation before the subject began their breath hold.During MRI, each subject's heart rate and oxygen saturation weremonitored using an MR-compatible monitoring system (Expression Model865214; Invivo Corporation, Orlando, Fla.).

¹²⁹Xe Spectroscopy

Dissolved-phase spectra were acquired using a 1.5 T GE scanner runningthe 15M4 EXCITE platform (GE Healthcare, Waukesha, Wis.). Subjects werefitted with a quadrature vest coil (Clinical MR Solutions, Brookfield,Wis.) tuned to 17.66 MHz. Spectra were acquired with the transmitfrequency tuned to selectively excite the dissolved-phase ¹²⁹Xe using a1.2 ms 2-lobe sinc pulse, applied at a frequency 3,832 Hz (217 ppm)above the gas-phase. Over the course of the 16 second breathingmaneuver, 802 free induction decays (FIDs) were acquired with 512samples per FID, echo time (TE)=0.932 ms, repetition time (TR)=20 ms,dwell time per point=32 μs, flip angle≈20°.

However, it is contemplated that the temporal resolution may bediminished from 20 ms to about 300 ms. Assuming that the highest heartrate likely to me encountered is 100 beats per minute (BPM), sampleswould need to be taken at twice this frequency or 3.33 Hz to meetNyquist criterion. This means that signals can be acquired about every300 ms. Reducing the temporal resolution (increasing TR) may provideseveral advantages. For example, spectral resolution can be increased bysampling the FID for a longer period (increasing the sampling rate).With a reduced temporal resolution, there is the opportunity to reducethe bandwidth (or increase the dwell time) which will increase SNR.

Also, or alternatively, the spectra can be acquired with a larger flipangle (i.e., about 90 degrees vs about 20 degrees). This can enhancesignal to noise ratio and result in more faithful spectral analysis.Also, by using 90 degree pulses all the dissolved phase magnetizationwill be destroyed after each read-out. Thus, the signals will besensitive to freshly diffused magnetization and will likely enhancesensitivity to delayed oxygenation in interstitial lung disease.

Spectroscopic Processing

Prior to fitting the spectra, two filtering steps were applied toimprove spectral SNR while minimizing the need to sacrifice the temporalresolution that was needed to capture the cardiopulmonary dynamics.First, the raw FIDs were processed using the Spectral Improvement byFourier Thresholding (SIFT) method. This involves Fourier transformingthe raw data along the indirect time dimension (time with respect to thebreath hold) and retaining only the coefficients that exceed apredetermined threshold. The data are then Fourier transformed backalong the indirect frequency dimension to undergo spectral curvefitting. This preprocessing thus filters the non-dominant frequenciesout of the indirect time dimension to smooth temporal changes betweenFIDS, while leaving the spectral-frequency domain intact. Thetime-domain SIFT-filtered FIDS were then averaged using a 5 FID slidingboxcar window filter and subsequently underwent complex fitting in thetime domain, using a custom MATLAB toolkit. See Robertson et al.Uncovering a third dissolved-phase ¹²⁹Xe resonance in the human lung:Quantifying spectroscopic features in healthy subjects and patients withidiopathic pulmonary fibrosis. Magnetic resonance in medicine. 2017;78(4):1306-1315; the contents of which is hereby incorporated byreference as if recited in full herein.

Although much prior literature has treated the dissolved phase ¹²⁹Xespectra as consisting of two simple Lorentzian RBC and barrierresonances, recent work has shown that the barrier resonance is morestructured. See Robertson et al. Uncovering a third dissolved-phase129Xe resonance in the human lung: Quantifying spectroscopic features inhealthy subjects and patients with idiopathic pulmonary fibrosis.Magnetic resonance in medicine. 2017; 78(4):1306-1315; the contents ofwhich is hereby incorporated by reference as if recited in full herein.This was addressed by Robertson et al. by allowing the barrier toconsist of two independent resonances. However, this requires fittingwith 4 additional degrees of freedom, which the SNR and spectralresolution of dynamically acquired data did not support. This wasevidenced by the approach returning ill-conditioned fits for dynamicallyacquired spectra. Instead, to allow for the extra, non-Lorentzianstructure of the barrier resonance, it was fit to a Voigt model. Thislineshape represents the convolution of a Lorentzian peak with aGaussian distribution and requires only one additional fitting degree offreedom. Specifically, it returns 2 distinct linewidth parameters—theLorentzian linewidth (FWHM) and Gaussian linewidth (FWHM). See, MarshallI, Higinbotham J, Bruce S, Freise A. Use of voigt lineshape forquantification of in vivo1H spectra. Magnetic resonance in medicine.1997; 37(5):651-657, the contents of which are hereby incorporated byreference as if recited in full herein.

The overall fitted signal can be calculated using Equation 1. Eachresonance is characterized by 4 spectral parameters: amplitude (α),frequency (f), phase (φ), and Lorentzian linewidth. For the barrierresonance, a 5^(th) parameter, the Gaussian linewidth (FWHM_(G)), wasalso extracted. Fitting of the barrier resonance was initialized withequal Lorentzian and Gaussian linewidths.

$\begin{matrix}{s_{fit} = {{a_{rbc}e^{{i\; \phi_{r\; {bc}}} + {2\; \pi \; {if}_{rbc}t}}e^{{- \pi}\; t \times {FWHM}_{rbc}}} + {a_{bar}e^{{i\; \phi_{bar}} + {2\; \pi \; {if}_{bar}t}}e^{{- \pi}\; t \times {FWHM}_{bar}}e^{{- 4}\; l\; n\; 2 \times t^{2}{FWHM}_{G_{bar}^{2}}}} + {a_{gas}e^{{i\; \phi_{gas}} + {2\; \pi \; i\; f_{gas}t}}e^{{- \pi}\; t\; \times {FWHM}_{gas}}}}} & {{EQN}(1)}\end{matrix}$

All frequencies (Hz) were reported as chemical shifts (in ppm) above thefrequency of the gaseous ¹²⁹Xe resonance.

Normalizing and Quantifying Cardiogenic Spectroscopic Changes in the RBCResonance

Although numerous quantitative parameters can be analyzed and extractedfrom the 3 resonances during the 3 periods of the breathing maneuver, wefocused specifically on characterizing temporal variations in ¹²⁹Xe RBCresonance occurring at the cardiac frequency (˜1 Hz). To extract theseparameters, the amplitude of the RBC peak was first corrected formagnetization decays caused by T1, and RF-induced depolarization duringthe breath-hold. These were incorporated into an apparent T1 decayconstant T1_(app) that was quantified by fitting the RBC amplitudewithin the breath-hold period to Ae^(−t/T1) ^(app) . The mean T1_(app)for all subjects was 13.6±2.7 s. This was then used to correct the RBCsignal and the remaining temporal changes in signal amplitude wereexpressed as a percentage change from baseline. Each of the RBC spectralparameters were further high-pass filtered with 0.5 Hz cutoff frequencyto remove any residual baseline variation. The corrected and filteredparameter plots were then fit to a sinusoid with phase offset:

½A _(pk-pk) sin(2πf _(c) t+φ),  EQN(5)

where A_(pk-pk) is the peak-to-peak amplitude, f_(c) is the cardiacfrequency, t is time in seconds, and φ is a phase off-set. The cardiacfrequency f_(c) was derived from each subject's RBC amplitudeoscillations and was used in the temporal fits of all other RBC spectralparameters (chemical shift, linewidth, and phase).

Statistical Analysis

Statistical analysis was performed in MATLAB. A Mann-Whitney-WilcoxU-test was used to determine if the differences between healthy normaland IPF subjects were statistically significant (P<0.05).

Example 1 Results

For each subject, the age, sex, pulmonary function test results, and themagnitude of the oscillations in the RBC spectral parameters aresummarized in Table 1 (FIG. 14).

Quantifying Static Spectral Parameters

Prior to analyzing the ¹²⁹Xe spectral dynamics, the static parameters,averaged over the first second of the breath-hold, were determined. Theresulting RBC and barrier fit parameters, as well as relevant derivedratios, are compared between the healthy and IPF cohorts in FIGS.12A-12D. The mean RBC:Barrier amplitude ratio (FIG. 12C) for healthyvolunteers was 0.58±0.12, which was significantly reduced in IPFpatients to 0.18±0.07 (P<0.001). The RBC frequency (FIG. 12A) was 1.5ppm lower in the IPF cohort (P=0.004) and its Lorentzian line width was1.7 ppm narrower (P=0.001). The barrier frequency (FIG. 12B) was also0.5 ppm lower in IPF (P=0.0025), and the Lorentzian component of itslinewidth 0.9 ppm smaller (P=0.006); the Gaussian linewidth did notdiffer from the healthy cohort (P=0.2). These differences contributed tothe phase difference between barrier FIG. 12B and RBC (FIG. 12A)resonances being 17.0° smaller compared to the healthy cohort (P=0.006).

¹²⁹Xe Spectral Changes Over the Course of the Breathing Maneuver

The spectral dynamics of all three ¹²⁹Xe resonances are displayed for arepresentative healthy volunteer (subject 6) in FIG. 1. The breathingmaneuver is reflected in each of the fit parameters, readily demarkingthe inhalation, breath-hold, and exhalation periods. As the subjectexhales, the gas resonance frequency shifts negatively by 0.11 ppm andits linewidth broadens by 0.1 ppm. In contrast, exhalation causes thebarrier resonance to shift positively by 0.06 ppm and its Lorentzianlinewidth to narrow by 0.29 ppm. The RBC resonance appears to beinfluenced by both inhalation and exhalation, primarily in itslinewidth, which, like the barrier, narrows slightly (0.37 ppm) duringexhalation. The RBC amplitude also exhibits a prominent periodicity at afrequency of 58 cycles per minute, which is consistent with thesubject's heart rate, recorded by pulse oximetry immediately prior toand after the acquisition (61 and 65 bpm, respectively). These dynamicsare also present, although more faintly, at the same frequency in theRBC chemical shift and phase.

FIG. 2 displays the same spectral dynamics, plotted for a subject withIPF (subject 13). Like in the healthy volunteer, the gas-phaseparameters reflect both the inhale and exhale dynamics, which are alsoclearly seen in the barrier resonance through an increasing chemicalshift but narrowing of both linewidth parameters upon exhalation. TheRBC resonance subtly shows the inhalation, while exhalation is welldemarked by its increasing chemical shift and Lorentzian linewidth,coupled with decreasing phase. In this IPF patient, the RBC amplitude isalso periodic at a frequency near subject's heart rate pre- andpost-scan (71 cycles per minute compared to 70 and 72 bpm,respectively). Interestingly, this cardiac periodicity is also prominentin both the RBC chemical shift and phase.

These cardiac dynamics affecting the RBC spectral parameters are betterappreciated in the normalized and detrended plots as shown for arepresentative healthy volunteer and several IPF patients in FIG. 13. Inthe healthy volunteer, the RBC amplitude varied peak-to-peak (pk-pk) at9.1%, while oscillations in the RBC chemical shift and phase remainedbelow 0.05 ppm and 1.5° respectively. By contrast, the first subjectwith IPF (IPF-13) not only exhibited more than 2-folder larger RBCamplitude variations (19.9% pk-pk), but also exhibited oscillations inRBC chemical shift that were nearly 6-fold larger at 0.29 ppm, whilephase varied nearly 4-fold more at 5.80. Such oscillations in RBCamplitude, frequency and phase were also notable in the other IPFsubjects depicted.

Amplitude of Oscillations Varies Between IPF and Healthy Subjects

The magnitude of the cardiogenic oscillations in the RBC spectralparameters are compared between healthy volunteers and IPF patients inFIG. 4. In the IPF versus healthy cohort, RBC amplitude variations werenearly twice as high (16.8±5.2% vs 9.7±2.9%; P=0.008), chemical shiftoscillations were more than 5-fold higher (0.43±0.33 ppm vs 0.083±0.05ppm; P<0.001), and RBC phase oscillations were more than 5-fold higher(7.7±5.6° vs 1.4±0.8°; P<0.001). Only the RBC linewidth was notstatistically different between the two cohorts (0.3±0.2 ppm vs 0.2±0.1ppm, P=0.1).

Discussion Benefits of Using a Barrier Voigt

The Voigt lineshape model was found to more robustly fit the¹²⁹Xe-barrier resonance dynamics than the “3-Lorentzian” fit (one RBC,two barrier). Although, the 3-Lorentzian model returns a lower residualerror than barrier Voigt when fitting high-resolution, high SNRspectra⁸, it is not well suited for the lower SNR and spectralresolution present in the dynamic ¹²⁹Xe acquisition. See Robertson etal. Uncovering a third dissolved-phase 129Xe resonance in the humanlung: Quantifying spectroscopic features in healthy subjects andpatients with idiopathic pulmonary fibrosis. Magnetic resonance inmedicine. 2017; 78(4):1306-1315. This is evidenced by highly variablefits for the two barrier resonances seen in FIG. 6B. By contrast, thebarrier Voigt model was able to capture the additional structure of thebarrier resonance, while remaining stable over the course of theacquisition. This is likely attributable to it requiring only oneadditional degree of freedom rather than the four required to fit thebarrier to two Lorentzian resonances. Moreover, the 2-componentdissolved-phase fitting of RBCs to a Lorentzian and barrier to a Voigtmodel leaves intact the current 3-compartment model of gas-exchange thatforms the basis of gas exchange imaging methods and CSSR analysis. SeeChang, Y V MOXE: a model of gas exchange for hyperpolarized ¹²⁹Xemagnetic resonance of the lung. Magnetic resonance in medicine. 2013;69(3):884-890.

Importantly, comparing the fits of a large average of data found thebarrier Voigt model to return similar RBC parameters as the 3-Lorentzianfit. The barrier Voigt model returned an RBC:Barrier ratio of 0.59±0.11for healthy volunteers that is reasonably consistent with previous 2-and 3-peak Lorentzian fitting of the dissolved resonances which are0.55±0.13 and 0.44±0.07 respectively, and correctly captures thestriking reduction in this ratio in subjects with IPF. See Kaushik etal., Measuring diffusion limitation with a perfusion-limitedgas—hyperpolarized 129Xe gas-transfer spectroscopy in patients withidiopathic pulmonary fibrosis. Journal of Applied Physiology. 2014;117(6):577-585; Robertson et al. Uncovering a third dissolved-phase129Xe resonance in the human lung: Quantifying spectroscopic features inhealthy subjects and patients with idiopathic pulmonary fibrosis.Magnetic resonance in medicine. 2017; 78(4):1306-1315.

Origins of Temporal Dynamics

The temporal changes in the ¹²⁹Xe spectra directly report on thephysiological dynamics of gas exchange in the lung and pulmonarycapillaries. It is striking to find that nearly all the spectralparameters reflect dynamics associated with the breathing maneuver. Thisis particularly well defined during exhalation, which is accompanied byan increasing gas-phase linewidth, combined with a correspondingnarrowing of both dissolved-phase peaks. This narrowing, which isinversely related to the apparent transverse relaxation time, T₂ ^(g),could suggest improving local field inhomogeneity, which, in the lung,is dominated by the bulk susceptibility difference of Δχ≈9 ppm betweenair and tissue²². See Chen et al. Spatially resolved measurements ofhyperpolarized gas properties in the lung in vivo. Part I: diffusioncoefficient. Magnetic resonance in medicine. 1999; 42(4):721-728. Duringexhalation, the passive compression of the lung moves air out of thealveolar sacs and reduces aggregate alveolar volume. See Hajari et al.Morphometric changes in the human pulmonary acinus during inflation.Journal of Applied Physiology. 2012; 112(6):937-943. This, in turn,increases the volume fraction of tissue relative to air while meancapillary diameter increases along with the average alveolar wallthickness. See Glazier et al. Measurements of capillary dimensions andblood volume in rapidly frozen lungs. Journal of Applied Physiology.1969; 26(1):65-76; Tsunoda et al. Lung volume, thickness of alveolarwalls, and microscopic anisotropy of expansion. Respiration physiology.1974; 22(3):285-296. Thus, during exhalation, fewer dissolved-phasexenon atoms reside near the air-tissue boundaries causing RBC andbarrier linewidths to narrow. By contrast, gas-phase xenon atoms are nowmore likely to reside near a tissue interface, and therefore thegas-phase linewidth increases.

The high-frequency dynamics of ¹²⁹Xe-RBC transfer provide an intriguingwindow on how the cardiac cycle affects gas exchange. The RBC signal inthese acquisitions arises predominantly from ¹²⁹Xe nuclei interactingwith RBCs in the pulmonary capillary bed. This strong localization stemsfrom using a relatively large flip angle (˜20°), combined with arepetition time that is short (TR=20 ms) in relation to the RBC transittime (˜750 ms). Thus, the magnetization of ¹²⁹Xe atoms in the dissolvedphase is quickly destroyed by RF pulses and can only be replenishedthrough continued diffusive gas transfer from the airspaces²⁶. However,once ¹²⁹Xe atoms move to larger vessels beyond the gas exchange units,such replenishment no longer occurs, and any residual magnetization isquickly destroyed by RF pulsing. Therefore, the fluctuations detected inthe RBC resonance provide evidence that ¹²⁹Xe-RBC transfer at thealveolar-capillary interface is temporally dependent on capillarypressure and blood volume oscillations driven by the cardiac cycle.

The oscillations in the RBC signal amplitude reflect a cyclic change inthe number of polarized ¹²⁹Xe atoms interacting with the RBCs over thecourse of the cardiac cycle. This observation is likely caused bycardiogenic fluctuations in capillary blood volume. The pulmonarycapillaries experience slightly elevated blood pressure at systole, witha concomitant decrease at diastole. See Rossvoll et al. Pulmonary venousflow velocities recorded by transthoracic Doppler ultrasound: relationto left ventricular diastolic pressures. Journal of the American Collegeof Cardiology. 1993; 21(7):1687-1696. Such pressure changes likelyaffect capillary blood volume, as recently demonstrated by synchrotronimaging over the course of a respiratory cycle. See Porra et al.Synchrotron Imaging Shows Effect of Ventilator Settings on Intra-breathCyclic Changes in Pulmonary Blood Volume. American Journal ofRespiratory Cell and Molecular Biology. 2017(ja). Here, the relative RBCamplitude fluctuations were found to be nearly two-fold larger insubjects with IPF, suggesting that in these patients, the relativechange in capillary blood volume over the cardiac cycle is larger thanin healthy volunteers. This is likely the result of these patientshaving significant regions of capillary destruction where RBC transferis absent. See Wang et al. Using hyperpolarized ¹²⁹Xe MRI to quantifyregional gas transfer in idiopathic pulmonary fibrosis. Thorax.2017:thoraxjnl-2017-210070; the contents of which is hereby incorporatedby reference as if recited in full herein. Thus, the additionalcapillary blood volume at systole is distributed to a relatively smallereffective capillary volume.

The observation of cardiogenic oscillations in the RBC chemical shift inpatients with IPF is particularly intriguing given that in vitro studieshave shown that the RBC frequency depends non-linearly on bloodoxygenation level, sO₂. See Norquay et al. ¹²⁹Xe chemical shift in humanblood and pulmonary blood oxygenation measurement in humans usinghyperpolarized 129Xe NMR. Magnetic resonance in medicine. 2017;77(4):1399-1408; Wolber et al. Hyperpolarized 129Xe NMR as a probe forblood oxygenation. Magnetic resonance in medicine. 2000; 43(4):491-496.Over the physiologically relevant range of sO₂=0.6-0.98, the RBCchemical shift increases sigmoidally by more than 4 ppm. This wouldsuggest that the observed pulsations in the RBC chemical shift of 0.43ppm reflect global sO₂ changes of order 0.07 in the pulmonarycapillaries, assuming a maximum sO₂ of 0.95. The fact that RBC frequencypulsations are seen in IPF, but not healthy subjects suggests this is apotentially unique signature of retarded diffusive transfer of oxygenacross the alveolar-capillary barrier. That is, as deoxygenated bloodenters the capillary beds at systole, it is slower to oxygenate inpatients with significant interstitial thickening. In a healthy normalvolunteer, capillary RBCs reach full oxygenation in about 250 ms, or athird of the total capillary transit time. See West et al. Respiratoryphysiology: the essentials. Lippincott Williams & Wilkins; 2012. Thus,in healthy volunteers the average sO₂ in RBCs experienced by ¹²⁹Xe isskewed towards full oxygenation. In contrast, the thicker interstitialbarrier tissues present in patients with IPF slow the diffusion of gasesand consequently, sO₂ levels in the pulmonary capillary beds are morebroadly distributed. Hence, while a healthy volunteer and subject withIPF may have the same distal O₂ saturation level, ¹²⁹Xe spectroscopydetects differences in the capillary sO₂ variation by probing thealveolar-capillary interface.

From a technical perspective, the cardiac pulsations are even moreprominent in the phase of the ¹²⁹Xe-RBC resonance. This metric, which islinearly related to chemical shift, provides a relatively clean signalthat may prove to be more robust. The observation of pulsations in ¹²⁹XeRBC frequency and phase may eventually prove to help differentiate thecauses of dyspnea attributable to interstitial disease from other causesof gas exchange impairment such as pulmonary vascular disease. SeeDahhan et al. Abnormalities in hyperpolarized ¹²⁹Xe magnetic resonanceimaging and spectroscopy in two patients with pulmonary vasculardisease. Pulmonary circulation. 2016; 6(1):126-131; the contents ofwhich is hereby incorporated by reference as if recited in full herein

Example 1 Conclusion

In this study, a method of acquiring, processing and analyzing ¹²⁹Xespectra over a simple 16 second spectroscopic acquisition and breathingmaneuver was successfully identified that yielded a series of novelparameters which can be used to further characterize gas exchange. Thecollected FIDs were fit to a Lorentzian for the RBC and gas resonancesand a Voigt lineshape for the barrier resonance. This accommodated theadditional structure of the barrier resonance, while limiting thedegrees of freedom such that the fitting algorithm converged even forthe lower SNR and spectral resolution of dynamic acquisitions.Spectroscopic fit parameters for each ¹²⁹Xe resonance were determinedwith 20 ms temporal resolution. Analysis of the static spectralparameters found features differentiating the IPF and healthy cohortsthat were largely consistent with previous studies. Their dynamicsshowed all three resonances to be sensitive to the breathing maneuver,with distinct changes in the RBC and gas linewidths. Most notably, theRBC amplitude, chemical shift, and phase were found to oscillate at thecardiac frequency. These oscillations were significantly larger inpatients with IPF than in healthy controls. Thus, careful analysis ofone or both static and dynamic ¹²⁹Xe spectra can potentially provide awide array of additional information that can help further discern thedifferent underlying causes of gas exchange impairment.

Example 2

As an increasing number of patients exhibit concomitant cardiac andpulmonary disease, limitations of standard diagnostic criteria are morefrequently encountered. In this Example 2, noninvasive ¹²⁹Xenon MRimaging and spectroscopy are used to identify patterns of regional gastransfer impairment and hemodynamics that are uniquely associated withchronic obstructive pulmonary disease (COPD), idiopathic pulmonaryfibrosis (IPF), left heart failure (LHF), and pulmonary arterialhypertension (PAH).

While ¹²⁹Xe imaging provides useful quantification of regionalfunctional burden, it is believed that a more detailed characterizationof whole-lung ¹²⁹Xe spectroscopic indices provide additional metricsthat may help to further discriminate the underlying pathologies. Thisarray of non-invasive imaging and spectroscopic markers of pulmonary gastransfer and hemodynamics derived from hyperpolarized ¹²⁹Xe can providea comprehensive and non-invasive phenotyping of cardiopulmonaryphysiology in individual patients.

In this Example 2, a comprehensive panel of non-invasive ¹²⁹Xe MRimaging and spectroscopy is applied to a cohort of patients with knownheart and lung disease in order to identify features that coulddifferentiate signatures of COPD, IPF, left heart failure (LHF), orpulmonary arterial hypertension (PAH). Hyperpolarized ¹²⁹Xe freelydiffuses from airspace to interstitial barrier tissues to RBCs. In thesecompartments, the ¹²⁹Xe atom exhibits distinct frequency shifts of 0ppm, 198 ppm, and 217 ppm, respectively. These properties can beexploited to allow 3D imaging and quantification of ¹²⁹Xe distributionin airspace (ventilation), its barrier uptake and RBC transfer togenerate maps. These maps can be color coded to represent differentsignal intensity levels with the central (green) bins representingvoxels in the normal reference range. ¹²9Xe spectra can be acquireddynamically, such as about every 20 ms, revealing cardiogenicoscillations of RBC amplitude (%) and frequency shift (ppm).

In this Example 2, healthy volunteers (n=23) and patients with COPD(n=8), IPF (n=12), LHF (n=6), and PAH (n=10) underwent ¹²⁹Xe gastransfer imaging and dynamic spectroscopy. For each patient, 3D mapswere generated to depict ventilation, barrier uptake, and red blood cell(RBC) transfer. Dynamic ¹²⁹Xe spectroscopy was used to quantifycardiogenic oscillations in the RBC signal amplitude and frequencyshift.

Compared to healthy volunteers, all patient groups exhibited decreasedventilation and RBC transfer (p≤0.01, p≤0.01). Patients with COPDdemonstrated more ventilation and barrier defects compared to all othergroups (p≤0.02, p≤0.02). In contrast, IPF patients demonstrated elevatedbarrier uptake compared to all other groups (p≤0.007) and increased RBCamplitude and shift oscillations compared to healthy volunteers(p=0.007, p≤0.01). Patients with COPD and PAH both exhibited decreasedRBC amplitude oscillations (p=0.02, p=0.005) compared to healthyvolunteers. LHF was distinguishable from PAH by enhanced RBC amplitudeoscillations (p=0.01).

COPD, IPF, LHF, and PAH each exhibit unique ¹²⁹Xe MR imaging and dynamicspectroscopy “signatures”. Each of the signatures can be described as aunique metric or graphic marker of a combination of different ¹²⁹Xeimaging and ¹²⁹Xe spectroscopy parameters, typically at least two ofeach, shown as using six such parameters. These metrics may help withdiagnostic challenges in cardiopulmonary disease and increaseunderstanding of regional lung function and hemodynamics at thealveolar-capillary level.

FIG. 15 provides a table of Demographic and Clinical Characteristicsstratified by Condition: IPF=idiopathic pulmonary fibrosis; COPD=chronicobstructive pulmonary disease; PAH=pulmonary arterial hypertension;6MWD=6-minute walk distance; PFT=pulmonary function test; PCWP=pulmonarycapillary wedge pressure; PVR=pulmonary vascular resistance; RVSP=rightventricular systolic pressure. Continuous variables presented as median(IQR); categorical variables presented as frequency (proportion)

Subject Recruitment

The protocol was approved by the Institutional Review Board of DukeUniversity Medical Center. Healthy volunteers, and patients with eitherCOPD, IPF, LHF, or PAH were recruited, and all provided written,informed consent. All healthy volunteers had no smoking history or knownrespiratory conditions. COPD was diagnosed using spirometry with apost-bronchodilator forced expiratory volume in one second (FEV₁)/forcedvital capacity (FVC)≤70% predicted. See Celli et al., Standards for thediagnosis and treatment of patients with COPD: a summary of the ATS/ERSposition paper. Eur Respir J, 2004. 23(6): p. 932-46. The diagnosis ofIPF was established according to ATS/ERS criteria, either from aconfirmed pattern of usual interstitial pneumonia (UIP) pattern on CT orfrom surgical lung biopsy. See Raghu et al., An officialATS/ERS/JRS/ALAT statement: idiopathic pulmonary fibrosis:evidence-based guidelines for diagnosis and management. Am J Respir CritCare Med, 2011. 183(6): p. 788-824. LHF was confirmed by echocardiogram.See Lang, Recommendations for Cardiac Chamber Quantification byEchocardiography in Adults: An Update from the American Society ofEchocardiography and the European Association of Cardiovascular Imaging(vol 28, pg 1, 2015). Journal of the American Society ofEchocardiography, 2016. 29(6): p. 521-521. PAH was defined according tothe World Health Organization criteria and diagnosed by right heartcatheterization with a resting mean pulmonary arterial pressure(mPAP)≥25 mmHg and a pulmonary capillary wedge pressure (PCWP)≤15 mmHg.See Simonneau, et al., Updated Clinical Classification of PulmonaryHypertension. Journal of the American College of Cardiology, 2009.54(1): p. S43-S54. All clinical tests were performed as a part ofroutine care. Pulmonary function tests (PFTs) were performed on allpatients and 83% of healthy volunteers to assess baseline pulmonaryfunction.

MRI Acquisition

¹²⁹Xe imaging and spectroscopy were acquired on either a 1.5 T (GE 15M4EXCITE) or a 3 T (SIEMENS MAGNETOM Trio) scanner. For each subject, 3Dimages were acquired using an interleaved radial acquisition of gas- anddissolved-phase data during a 15 second breath-hold. See Kaushik, S. S.,et al., Probing the regional distribution of pulmonary gas exchangethrough single-breath gas-and dissolved-phase Xe-129 MR imaging. Journalof Applied Physiology, 2013. 115(6): p. 850-860, the contents of whichare hereby incorporated by reference as if recited in full herein. Datawere acquired at an echo time that allowed the two-dissolved phasecompartments to be decomposed using the 1-point Dixon method. SeeKaushik et al., Single-breath clinical imaging of hyperpolarized (129)Xein the airspaces, barrier, and red blood cells using an interleaved 3Dradial 1-point Dixon acquisition. Magn Reson Med, 2016. 75(4): p.1434-43, the contents of which are hereby incorporated by reference asif recited in full herein. This generated 3D images of the gas, barrier,and RBC components with 2.8 mm isotropic voxels. Subjects also underwentdynamic spectroscopy during which ¹²⁹Xe free induction decays (FIDs)were collected every 20 ms (TE=0.932 ms, flip angle≈20°, dwell time=32μs, 512/1024 points) during a breath-hold. See Bier et al., A protocolfor quantifying cardiogenic oscillations in dynamic (129) Xe gasexchange spectroscopy: The effects of idiopathic pulmonary fibrosis. NMRBiomed, 2018: p. e4029, the contents of which are hereby incorporated byreference as if recited in full herein.

Quantitative Processing and Analysis

3D images of each compartment were rendered into quantitative maps andcast into color clusters using thresholds derived from a healthyreference cohort. See Wang, Z., et al., Quantitative analysis ofhyperpolarized 129 Xe gas transfer MRI. Med Phys, 2017. 44(6): p.2415-2428; He, M., et al., Using Hyperpolarized 129Xe MRI to Quantifythe Pulmonary Ventilation Distribution. Acad Radiol, 2016. 23(12): p.1521-1531, the contents of which are hereby incorporated by reference asif recited in full herein. The resulting binning maps depict ¹²⁹Xeventilation, barrier tissue uptake, and RBC transfer. Each of these mapswere quantified by calculating the percentage of the lung exhibitingsignal defects and high signal. See Wang, Z., et al., Quantitativeanalysis of hyperpolarized 129 Xe gas transfer MRI. Med Phys, 2017.44(6): p. 2415-2428, the contents of which are hereby incorporated byreference as if recited in full herein. The dynamically acquired FIDswere fit in the time domain to determine the gas, barrier, and RBCspectral parameters. See Bier, E. A., et al., A protocol for quantifyingcardiogenic oscillations in dynamic (129) Xe gas exchange spectroscopy:The effects of idiopathic pulmonary fibrosis. NMR Biomed, 2018: p.e4029, the contents of which are hereby incorporated by reference as ifrecited in full herein. The time dependent RBC signal was detrended andthe cardiogenic oscillations in its amplitude and frequency shift werequantified by their peak-to-peak value relative to the mean. See, again,Bier, E. A., et al., A protocol for quantifying cardiogenic oscillationsin dynamic (129) Xe gas exchange spectroscopy: The effects of idiopathicpulmonary fibrosis. NMR Biomed, 2018: p. e4029. Imaging andspectroscopic findings were compared across all cohorts.

Statistical Methods

Imaging and spectroscopic features were compared between cohorts. Allcomputations were performed using JMP 14 (SAS Institute Inc, Cary,N.C.). First, a one-way analysis of variance was performed using thenon-parametric Kruskal-Wallis. When a significant difference wasdetected, the Mann Whitney U-test was further used for pairwiseanalysis. Statistical significance was claimed for p<0.05.

Study Cohort

This study included 23 healthy volunteers, 8 patients with COPD, 12 withIPF, 6 with LHF, and 10 with PAH. Subject demographics and PFT resultsare summarized in FIG. 15.

3D-isotropic images of ¹²⁹Xe in the gas, barrier, and RBC compartmentswere acquired on 19 healthy volunteers and all patients. Dynamicspectroscopy was acquired on 13 healthy volunteers, 6 patients withCOPD, 8 with IPF, 5 with LHF, and 10 with PAH. Subjects were excludedfrom either imaging or spectral analysis if the acquisition did notachieve adequate SNR required for reliable quantification.

Identifying Disease-Specific Imaging-Derived Metrics

Representative ventilation and gas transfer maps from subjects in eachgroup are depicted in FIG. 16 along with the derived quantitativemetrics. For each map, the percentages of voxels falling in the defect,low, and high bins are reported. In the healthy volunteer, the majorityof the ¹²⁹Xe signal in all three compartments fell within ±1 standarddeviation from the mean of the reference distribution and thus, in the“normal” green color bins. In contrast, the COPD subject exhibitedsignificant defects in all 3 compartments —ventilation, barrier, andRBC, indicated by the red color bins. The IPF subject exhibitedrelatively normal ventilation, but significant areas of high barrieruptake, accompanied by defects in RBC transfer in the lower lobes. Boththe LHF and PAH subjects exhibited slight ventilation defects,relatively normal barrier, but more significant deficits in RBCtransfer. Ventilation, barrier uptake, and RBC transfer maps ofrepresentative subjects from each cohort. The color bins representsignal intensity, with red for the lowest and blue/purple for thehighest and green representing voxels in the healthy reference range.Each map is quantified by the defect (D), low (L), and high (H)percentage, calculated respectively as the voxel fraction of the lowest,second lowest, and the highest two bins for each map.

FIGS. 17A-17D evaluate these imaging features quantitatively across thecohorts, comparing the percentages of ventilation defects, RBC defects,barrier defects and high barrier. Ventilation defect (FIG. 17A), RBCdefect (FIG. 17B), Barrier defect (FIG. 17C) and Barrier high percentagecomparisons for all cohorts (FIG. 17D). Asterisks mask a significantlyincreased (red-R) or decreased (green-G) value compared to all othercohorts. Compared to healthy subjects, all disease cohorts showedincreased ventilation defect (p≤0.01) and RBC defect (p≤0.01). COPD wascharacterized by significantly elevated percentages of ventilationdefects (p≤0.02) and barrier defects (p≤0.02). IPF uniquely exhibitedreduced barrier defects (p≤0.02) but elevated percentages of highbarrier (p≤0.007). PAH and LHF exhibited slightly elevated ventilationdefects and modestly elevated RBC defects. Compared to healthy subjects,all patient groups exhibited a larger percentage of defects inventilation (p≤0.01 for all comparisons) and RBC transfer (p≤0.01 forall comparisons). The COPD cohort stood out for exhibiting the largestpercentages of ventilation defects (41.5±22.6%, p≤0.02 for allcomparisons) and was the only one to show defects in barrier uptake(10.4±7.1%, p≤0.02 for all comparisons). By contrast, IPF patients weredistinguished from the other groups by the largest percentage of voxelswith high ¹²⁹Xe uptake in the barrier tissue (39.8%, p≤0.007 for allcomparisons). IPF subjects exhibited only modest ventilation defects(11.5±6.7%, p=0.0003 vs healthy) but substantial RBC defects (11.3±6.7%,p=0.0001 vs healthy). LHF and PAH patients presented with similarimaging characteristics with mildly elevated ventilation defects (LHF:11.7±6.2%, p=0.01 vs healthy; PAH: 8.4±4.7%, p=0.01 vs healthy) andincreased RBC transfer defects (LFH: 13.3±10.2%, p=0.01 vs healthy; PAH:14.5±9.3%, p=0.002 vs healthy).

Disease-Specific Spectroscopy-Derived Metrics

FIGS. 18A and 18B show the detrended RBC signal amplitude and shiftoscillations for representative subjects from each group demonstratecardiogenic oscillations. Notably, the RBC signal amplitudes (FIG. 18A)for each patient oscillate at a frequency identical to his/her heartrate. The IPF patient also exhibits such cardiogenic oscillationsprominently in the RBC frequency shift. Both the IPF and LHF patientexhibit enhanced RBC amplitude oscillations. By contrast, RBC signaloscillations are diminished in both the PAH and COPD patients. Only theIPF patient exhibits oscillations in the RBC shift (FIG. 18B).

FIGS. 19A and 19B show the group-wise comparison of the cardiogenic RBCamplitude and shift metrics. In healthy subjects, the RBC amplitude(FIG. 19A) oscillated at a height of 10.0±2.6% peak-to-peak with verylittle RBC shift oscillation (0.07±0.05 ppm). The RBC shift (FIG. 19B)only oscillates significantly in the IPF cohort (0.46±0.33 ppm, p≤0.01for all comparisons). IPF patients also exhibited larger RBC amplitudeoscillations (16.7±5.5%, p=0.007) compared to healthy volunteers. RBCamplitude oscillations were diminished in both COPD and PAH compared tohealthy volunteers (COPD: 5.5±4.7%, p=0.02; PAH: 6.0±3.6%, p=0.005). Insubjects with LHF, the RBC amplitude oscillations were larger than inhealthy volunteers, but this did not reach statistical significance(13.0±5.1%, p=0.2). However, these oscillations were significantlyhigher compared to subjects with PAH (p=0.01). Thus, FIGS. 19A and 19Bshow RBC amplitude and frequency shift oscillations, respectively,compared across cohorts. Gray (G) asterisks mark a significantdifference between cohorts and red (R) asterisk marks increased valuecompared to all other cohorts. Compared to healthy subjects, COPD(p=0.02) and PAH (p=0.005) exhibited decreased RBC amplitudeoscillations, while they were increased in IPF (p=0.007). Moreover, inLHF the RBC amplitude oscillations were significantly increased comparedto PAH (p=0.01). IPF patients exhibited significantly increased RBCshift oscillations compared to all other cohorts (p≤0.01)

Discussion

¹²⁹Xe Biomarkers Distinguish Different Disease Phenotypes

In this study, unique ¹²⁹Xe MR imaging and spectroscopy signatures forpatients with COPD, IPF, PAH, and LHF were identified. COPD wascharacterized by significantly elevated ventilation and barrier defectpercentages compared to all other disorders, as well as diminished RBCamplitude oscillations. However, in COPD ventilation defect percentagevaried widely within the cohort, consistent with the heterogeneity ofthe disease. See, Pike et al., Regional Heterogeneity of ChronicObstructive Pulmonary Disease Phenotypes: Pulmonary He-3 MagneticResonance Imaging and Computed Tomography. Copd-Journal of ChronicObstructive Pulmonary Disease, 2016. 13(5): p. 601-609, the contents ofwhich are hereby incorporated by reference as if recited in full herein.In contrast, IPF was characterized primarily by elevated barrier uptake,virtually absent barrier defect percentage, elevated RBC amplitudeoscillations, and prominent oscillations in RBC shift. PAH and LHFpresented with similar imaging characteristics (slight elevations inventilation, barrier, and RBC defect percentages compared to healthyvolunteers). However, PAH was distinguished from LHF by RBC amplitudeoscillations that were lower than in healthy subjects, whereas in LHFsuch oscillations were enhanced. All four disease cohorts showedsignificant RBC transfer defects.

These imaging findings are consistent with previous studies that haveidentified increased ventilation defects in patients with COPD. See Wanget al., Hyperpolarized (129) Xe gas transfer MRI: the transition from1.5T to 3T. Magn Reson Med, 2018; Qing et al., Assessment of lungfunction in asthma and COPD using hyperpolarized 129Xe chemical shiftsaturation recovery spectroscopy and dissolved-phase MRI. NMR Biomed,2014. 27(12): p. 1490-501; and Virgincar et al., Quantitative analysisof hyperpolarized 129Xe ventilation imaging in healthy volunteers andsubjects with chronic obstructive pulmonary disease. NMR Biomed, 2013.26(4): p. 424-35, the contents of which are hereby incorporated byreference as if recited in full herein.

The observation that in COPD barrier uptake is also diminished is a newfinding, likely reflecting emphysematous lung destruction and loss ofsurface area for gas exchange. This loss further leads to diminished RBCtransfer. In IPF, the disease is characterized by increased barrieruptake with defects in RBC transfer primarily in the lung bases. SeeKaushik et al., Single-breath clinical imaging of hyperpolarized (129)Xein the airspaces, barrier, and red blood cells using an interleaved 3Dradial 1-point Dixon acquisition. Magn Reson Med, 2016. 75(4): p.1434-43; Kaushik et al., Measuring diffusion limitation with aperfusion-limited gas—hyperpolarized 129Xe gas-transfer spectroscopy inpatients with idiopathic pulmonary fibrosis. J Appl Physiol, 2014.117(6): p. 577-85; Wang et al., Hyperpolarized (129) Xe gas transferMRI: the transition from 1.5T to 3T. Magn Reson Med, 2018; Wang et al.,Using hyperpolarized (129)Xe MRI to quantify regional gas transfer inidiopathic pulmonary fibrosis. Thorax, 2018. 73(1): p. 21-28; andKaushik et al., Probing the regional distribution of pulmonary gasexchange through single-breath gas-and dissolved-phase Xe-129 MRimaging. Journal of Applied Physiology, 2013. 115(6): p. 850-860, thecontents of which are hereby incorporated by reference as if recited infull herein. Furthermore, the study provides important context for priorwork showing that cardiogenic oscillations in ¹²⁹Xe RBC amplitude andshift are significantly enhanced in patients with IPF relative tohealthy controls. See Kaushik et al., Measuring diffusion limitationwith a perfusion-limited gas—hyperpolarized 129Xe gas-transferspectroscopy in patients with idiopathic pulmonary fibrosis. J ApplPhysiol, 2014. 117(6): p. 577-85; and Bier et al., A protocol forquantifying cardiogenic oscillations in dynamic (129) Xe gas exchangespectroscopy: The effects of idiopathic pulmonary fibrosis. NMR Biomed,2018: p. e4029, the contents of which are hereby incorporated byreference as if recited in full herein. Having now acquired such data inthis broader cohort suggests that the RBC shift oscillations are, thusfar, unique to IPF, and are not observed COPD, LHF, and PAH. Moreover,the enhanced RBC amplitude oscillations seen in in IPF are onlyadditionally seen in LHF, suggesting that this is a marker ofpost-capillary PH.

Alveolar-Capillary Interface Models Depicting Disease Phenotypes

FIG. 20 illustrates diagrammatic conceptual architectures of thealveolar-capillary interface to aid in interpreting the ¹²⁹Xe imagingand spectroscopic biomarkers across disease states. The diagramsillustrate the alveoli, capillary blood vessel, interstitial barriertissues, RBCs, and ¹²⁹Xe atoms. For each disease state the anticipatedeffect on the ¹²⁹Xe biomarker (ventilation, barrier and RBC) is shown.These conceptual diagrams may aid in interpreting the patterns of ¹²⁹XeMRI and spectroscopic signatures of each disease in the context of gastransfer physiology, without limitation to the invention. In a healthysubject, ¹²⁹Xe atoms freely diffuse into the alveoli and into thealveolar-capillary interface, translating into images reflecting anormal range of ventilation, barrier uptake and RBC transfer. In COPD,chronic airway inflammation and small airway obstruction createventilation defects, while the loss of alveolar surface area associatedwith emphysema results in diminished uptake of ¹²⁹Xe in the interstitialbarrier tissues. See Barnes et al. Systemic manifestations andcomorbidities of COPD. European Respiratory Journal, 2009. 33(5): p.1165-1185, the contents of which are hereby incorporated by reference asif recited in full herein. This is associated with a concomitantdecrease in RBC transfer, although many patients exhibitdisproportionately worse RBC transfer that may reflect an additionalloss of vasculature. See Rahaghi, F. N., E. J. R. van Beek, and G. R.Washko, Cardiopulmonary Coupling in Chronic Obstructive PulmonaryDisease The Role of Imaging. Journal of Thoracic Imaging, 2014. 29(2):p. 80-91, the contents of which are hereby incorporated by reference asif recited in full herein. By contrast, in IPF, interstitial fibrosiscauses ¹²⁹Xe uptake in barrier tissues to increase. See Lederer et al.Idiopathic Pulmonary Fibrosis. N Engl J Med, 2018. 379(8): p. 797-798,the contents of which are hereby incorporated by reference as if recitedin full herein. This, in turn, causes diffusion limitation, which inaddition to likely perfusion deficits, serves to decrease RBC transfer.See Wang, J. M., et al., Using hyperpolarized (129)Xe MRI to quantifyregional gas transfer in idiopathic pulmonary fibrosis. Thorax, 2018.73(1): p. 21-28, the contents of which are hereby incorporated byreference as if recited in full herein. When such destruction isaccompanied by a preserved stroke volume, it will produce largerrelative capillary blood volume oscillations between systole anddiastole; this can manifest as larger RBC amplitude oscillations. In thesetting of pulmonary hypertension (PH), left heart failure (LHF) ischaracterized by post-capillary impedance (predominantly from pulmonaryvenous PH). Because the high impedance originates downstream of thecapillary beds, it is associated with larger capillary blood volumeoscillations during the cardiac cycle, again resulting in largerspectroscopic RBC amplitude oscillations. It is less clear what causesthe defects in RBC transfer, but it is known that LHF patients candevelop gas exchange abnormalities including a decrease in DLCO that isthought to be secondary to chronic damage from pulmonary venouscongestion. See Olson et al. Impaired Pulmonary Diffusion in HeartFailure With Preserved Ejection Fraction. Jacc-Heart Failure, 2016.4(6): p. 490-498; and Guazzi, M., Alveolar Gas Diffusion Abnormalitiesin Heart Failure. Journal of Cardiac Failure, 2008. 14(8): p. 695-702,the contents of which are hereby incorporated by reference as if recitedin full herein. And finally, it is contemplated that PAH can becharacterized by increased pre-capillary impedance resulting from, interalia, remodeling and obliteration of the pulmonary arterioles, which canresult in a loss of alveolar membrane diffusing capacity and pulmonarycapillary blood volume. See Farha et al., Loss of alveolar membranediffusing capacity and pulmonary capillary blood volume in pulmonaryarterial hypertension. Respiratory Research, 2013, 14, the contents ofwhich are hereby incorporated by reference as if recited in full herein.While these features in PAH may not be expected to directly impactventilation or diffusive barrier uptake, they can cause RBC transferdefects and increase impedance to flow occurring upstream of thecapillary bed. This, in turn, can reduce the pulmonary capillary bloodvolume and the cardiogenic blood volume oscillations in the capillarybed. This can result in diminished RBC signal amplitude oscillations,which appears, at least at the present time, to be the feature that moststrongly differentiates pre-capillary from post-capillary PH.

Differentiating Cardiopulmonary Diseases in the Clinical Setting

Taken together, this combination of non-invasive ¹²⁹Xe MR imaging andspectroscopic parameters allows interrogation of gas transfer at thealveolar capillary level that appears useful, not only forcharacterizing and quantifying disease burden, but identifyingsignatures that may help differentiate cardiopulmonary disorders, statesor diseases. A potential output of this approach this is shown in FIG.21, which shows radar plots (charts) of 4 key imaging features and 2 keyspectroscopic features—ventilation defect, barrier defect, high barrieruptake, RBC defects, and RBC amplitude and shift oscillations.Integrating these features for each disease group can provide an initialgraphic output of displaying these phenotypes in a visually distinctway. Generating such plots for individual patients can provide apowerful protocol to identify the primary phenotypes that should beconsidered. The radar chart is a graphical method of displayingmultivariate ¹²⁹Xe data in the form of a two-dimensional chart of threeor more quantitative variables, with one or more different measurementunits, such as percentage and ppm represented on axes starting from thesame point. Of course, other outputs may be used such as, but notlimited to, to a parallel coordinates plot, with the axes arrangedradially.

In FIG. 21, the radar plots display the primary ¹²⁹Xe MR imaging andspectroscopic signatures associated with patients with COPD, IPF, LHF,and PAH. Here the mean cohort values of the key markers are plotted onone of the 6 radials—ventilation defect, barrier defect, barrier high,RBC defect percentages derived from imaging, and RBC shift oscillationand amplitude oscillation from spectroscopy.

In addition to differentiating between various cardiopulmonaryconditions, ¹²⁹Xe MRI may be useful in determining the underlying causeof dyspnea in patients with mixed cardiopulmonary disease, e.g., inpatients who have concomitant diseases. This is a common clinicalsituation in an aging population, where many individuals may haveconcomitant COPD and LHF that complicate ILD or PAH. See Hoeper et al.,Elderly patients diagnosed with idiopathic pulmonary arterialhypertension: results from the COMPERA registry. Int J Cardiol, 2013.168(2): p. 871-80, the contents of which are hereby incorporated byreference as if recited in full herein. Furthermore, as early diagnosisis increasingly emphasized in disorders such as ILD and PAH (seeCosgrove, G. P., et al., Barriers to timely diagnosis of interstitiallung disease in the real world: the INTENSITY survey. BMC Pulm Med,2018. 18(1): p. 9; and Lau et al. Early detection of pulmonary arterialhypertension. Nat Rev Cardiol, 2015. 12(3): p. 143-55), ¹²⁹Xespectroscopic indices may provide a sensitive probe for early diagnosisand disease progression, the contents of which are hereby incorporatedby reference as if recited in full herein. Furthermore, the RBC transfersignal depicts the ultimate disease burden for gas transfer function,and therefore might be used in evaluation of disease progression andtherapy response. See Mammarappallil, J. G., et al., New Developments inImaging Idiopathic Pulmonary Fibrosis With Hyperpolarized Xenon MagneticResonance Imaging. J Thorac Imaging, 2019. 34(2): p. 136-150, thecontents of which are hereby incorporated by reference as if recited infull herein. Given the limitations of current diagnostic testing, theinformation provided by ¹²⁹Xe gas transfer imaging and dynamicspectroscopy has the potential to improve patient care.

Study Comments

Several limitations apply to study of Example 2 when comparing ¹²⁹Xe MRimaging and spectroscopic signatures across cardiopulmonary conditions.First, the heterogeneity and possible comorbidities of patients in eachdisease cohort may have limited the ability to identify patterns in¹²⁹Xe imaging and spectroscopy and contribute to variations in eachgroup. For example, all PAH patients were undergoing PAH targetedtreatment, and many did not have a recent right heart catheterization,which may have limited the severity of their PAH at the time of the¹²⁹Xe study. Furthermore, while this study aimed to recruit patientswith isolated LHF as a model for post-capillary impedance, several mayhave also had right heart failure given the common pathogenic evolutionfrom left heart dysfunction to right heart dysfunction over time. SeeRosenkranz et al., Left ventricular heart failure and pulmonaryhypertension. Eur Heart J, 2016. 37(12): p. 942-54, the contents ofwhich are hereby incorporated by reference as if recited in full herein.In fact, this phenotypic evolution may partly explain the largevariation in RBC amplitude oscillation exhibited by our LHF cohort (Max:21.5%, Min: 8.0%, SD: 5.1%). Another limitation is that the subjectscans were conducted at different platforms with two field strengths.The quantification method, using a healthy reference group constructedunder the same acquisition protocol, was designed to incorporate thepotential factors such as T₁ and T₂* decay, which may affect the gastransfer measurements. See Wang et al. Quantitative analysis ofhyperpolarized 129 Xe gas transfer MRI. Med Phys, 2017. 44(6): p.2415-2428, the contents of which are hereby incorporated by reference asif recited in full herein. However, these and other factors constrainedthe size of the healthy reference cohorts, which were also significantlyyounger than the typical patients in the cohorts. Since the aging lungis reported to undergo physiological changes that could impact gastransfer functions, future studies will benefit from constructing alarger and age-controlled healthy population. See Janssens, J. P., J. C.Pache, and L. P. Nicod, Physiological changes in respiratory functionassociated with ageing. Eur Respir J, 1999. 13(1): p. 197-205, thecontents of which are hereby incorporated by reference as if recited infull herein.

Conclusions

In this Example 2 study, we applied ¹²⁹Xe gas transfer imaging andspectroscopy on healthy subjects and patients with COPD, IPF, LHF, andPAH. As a non-invasive and non-ionizing tool, hyperpolarized ¹²⁹Xegas-transfer MRI provides a fundamentally new approach to directly imageregional function while also capturing hemodynamics at thealveolar-capillary level. The identified unique imaging andspectroscopic signatures for each of these diseases may help overcomesome of the diagnostic challenges faced by clinicians treating patientswith cardiopulmonary disease. ¹²⁹Xe gas transfer imaging andspectroscopy is a promising technology in characterizing cardiopulmonarydisease pathophysiology and with further validation in larger studies,it is believed that this can contribute to a comprehensive understandingof the multifactorial pathogenesis of dyspnea and/or developingpersonalized treatment approaches.

Example 3

In this Example 3, experiments were carried out to evaluate whetherpre-capillary (PAH) versus post-capillary (PHpost) origins of PH can bedistinguished while accounting for concomitant lung disease like ILD orCOPD.

In this study, regional gas exchange and hemodynamics withhyperpolarized ¹²⁹Xe MRI were obtained. The study obtained single-breath3D MRI images of ventilation, barrier and blood (RBC compartment) thatidentify defects in the gas exchange region of the lungs and singlebreath-dynamic spectroscopy of RBC peak amplitude and chemical shift(ppm) over time.

Experiment Subject Recruitment

Healthy: 22; ILD: 12: PAH: 10, Left Heart Failure: 6 (surrogate forpost-capillary PH): COPD: 8.

Methods: Acquired ¹²⁹Xe gas exchange imaging and dynamic spectroscopyfor each subject.

FIG. 22 are representative ventilation, barrier and RBC images andassociated amplitude and chemical shift spectra of healthy lungs. TheRBC defect was 2%, the RBC low: 5%. The peak amplitude was at 10.3%while the frequency oscillation was at 0.02 ppm.

FIG. 23 are representative of ventilation, barrier and RBC images andassociated amplitude and chemical shift spectra of a subject with PAH.The RBC defect was 11%, the RBC low: 33%. The peak amplitude was at 4.3%while the frequency oscillation was at 0.06 ppm.

FIG. 24 are representative of ventilation, barrier and RBC images andassociated amplitude and chemical shift spectra of a subject with ILD.The RBC defect was 19%, the RBC low: 20%. The peak amplitude was at12.8% while the frequency oscillation was at 0.31 ppm.

RBC amplitude oscillations were used to identify healthy, pre- andpost-capillary PH. FIG. 25 is a graph of RBC amplitude oscillation (%)for healthy and different disease states of the lung(s) including ILD,PAH, PHpost and COPD. As shown by the appended text at the right side ofthe graph, the various lines, from top (hightst RBC amplitudeoscillation) to bottom (lowest), indicate likely PHpost or ILD, possiblePHpost or ILD, excluded, possible arteriopathy, and likely ateriopathy.

FIG. 26 is a graph of True Positive Rate versus False Positive Rateusing ROC curve of RBC amplitude oscillation to determine thresholds toseparate/distinguish healthy, pre- and post-capillary PH. The ROC curvearea is shown with best thresholds: 7.9

FIG. 27 is a set of 3D images (ventilation, barrier and RBC) of healthyand different disease cohorts illustrating lung maps showing metricsthat can further distinguish the different disease cohorts (ILD, PAH,PHpost, COPD).

FIG. 28 is a schematic illustration of a diagnostic analysis protocol(i.e., model) of defined parameters that can be used to identify adisease state with ventilation, barrier and RBC defect percentages fromthe 3-D lung maps along with the dynamic spectroscopy parameters of RBCamplitude and frequency oscillations. The model correctly classified 34of 40 subjects (85%) who had both imaging and spectroscopy data.

FIG. 29 is an example application of image and spectra metric parametersof Subject A that was used for a diagnostic analysis protocol withventilation, barrier and RBC defect percentages from the 3-D lung mapsalong with the dynamic spectroscopy parameters of RBC amplitude and RBCfrequency oscillation.

FIG. 30 illustrates the diagnostic analysis applied to the metricparameters of Subject A illustrating various diagnostic decisions madebased on RBC amplitude oscillation, RBC defect percentage, andventilation and barrier defect percentages.

FIG. 31 is an example application of image and spectra metric parametersof Subject B that used the diagnostic analysis protocol withventilation, barrier and RBC defect percentages from the 3-D lung mapsalong with the dynamic spectroscopy parameters of RBC amplitude and RBCfrequency oscillation.

FIG. 32 illustrates the diagnostic analysis applied to the metricparameters of Subject B illustrating various diagnostic decisions madebased on RBC amplitude oscillation, RBC defect percentage, andventilation and barrier defect percentages.

Conclusion, Example 3

The diagnostic analysis model shows promise to distinguish pre-capillary(PAH) versus post-capillary (PHpost) origins of PH, while accounting forconcomitant lung disease such as ILD or COPD. It is noted that PAHpatients were all on standard therapy, PH was not specifically ruled outfrom the ILD and COPD cohorts. In the future, prospective testing on alarger cohort undergoing same-day right heart catheterization as a goldstandard to measure sensitivity and specificity for the ability of ¹²⁹Xemetrics to detect PAH may be desireable.

In some embodiments of the present invention have been illustratedherein by way of example. Many variations and modifications can be madeto the embodiments without substantially departing from the principlesof the present invention. All such variations and modifications areintended to be included herein within the scope of the presentinvention, as set forth in the following claims.

1. A method of generating dynamic spectroscopy parameters, comprising:obtaining a ¹²⁹Xe spectrum of free induction decays (FIDs) ¹²⁹Xe NMRsignal of a gas exchange region of a lung or lungs of a subject during abreathing maneuver comprising one or more of inspiration/inhale,breath-hold or expiration/exhale; fitting the obtained ¹²⁹Xe spectrum ofthe FIDs with a curve fitting function, wherein the ¹²⁹Xe spectrum ismodeled with one or more non-Lorentzian line shapes; and electronicallygenerating a plurality of dynamic ¹²⁹Xe spectral parameters based on thefitting, wherein the plurality of dynamic ¹²⁹Xe spectral parametersinclude plots over time of at least one of: (i) barrier amplitude,barrier chemical shift (ppm), one or more barrier full width at halfmaximum (FWHM)(ppm) parameters; (ii) gas amplitude, gas chemical shift(ppm), gas FWHM (ppm), and gas phase (degrees); and (iii) red blood cell(RBC) amplitude, RBC chemical shift (ppm), RBC FWHM (ppm), and RBC phase(degrees).
 2. The method of claim 1, further comprising, before thefitting and generating steps, extracting temporal variations in ¹²⁹XeRBC resonance occurring at a cardiac frequency.
 3. The method of claim1, wherein the fitting is carried out with a ¹²⁹Xe barrier resonancemodeled as a Voigt line shape and ¹²⁹Xe RBC and ¹²⁹Xe gas-phaseresonances are each modeled using a Lorentzian line shape, and whereinthe barrier resonance is characterized by both a Lorentzian FWHMparameter and a Gaussian FWHM (FWHM_(G)) (ppm) parameter.
 4. The methodof claim 1, further comprising adjusting amplitude “A_(RBC)” of the RBCamplitude plot by multiplying by:(V_stroke_ref/V_stroke)*(PEV/PEV_ref), where V_stroke_ref is a referencestroke volume like 94 ml or 95 ml (adult), V_stroke is a subject'sactual stroke volume, PEV_ref is a reference pulmonary exchange volume,and PEV is the subject's measured pulmonary exchange volume.
 5. Themethod of claim 2, further comprising correcting amplitude of the RBCamplitude plot of the ¹²⁹Xe spectral parameter for magnetization decayscaused by T1 and RF-induced depolarization during a breath-hold periodof the breath-hold of the breathing maneuver by dividing the RBCamplitude “A” by a calculated apparent T1 decay constant (T1app),wherein T1app is quantified by fitting RBC amplitude over time “t” toe^(−t/T1) ^(app) .
 6. The method of claim 1, further comprisingdetrending amplitudes of the ¹²⁹Xe spectral parameters, then calculatingpeak-peak variation over time.
 7. The method of claim 2, furthercomprising calculating temporal changes in signal amplitude of the RBCamplitude (A) as a percentage change from baseline (rbc_amp_percent):rbc_amp_percent=(rbc_amp−A*exp(−t/T1_(app)))/(A*exp(−t/T1_(app))) whereT1_(app) is a T1 decay constant and t is time (seconds).
 8. The methodof claim 2, further comprising calculating temporal changes in signalamplitude of the RBC amplitude (A) using peak to peak analysis of adifference between a maximum and a minimum in an oscillating signal ofthe RBC amplitude.
 9. The method of claim 1, further comprisinghigh-pass filtering each of the RBC amplitude, RBC chemical shift, RBCphase and RBC FWHM with a 0.5 Hz cutoff frequency to thereby removeresidual baseline variation and provide filtered parameter plots of theRBC spectral parameters.
 10. The method of claim 9, further comprisingfitting the filtered parameter plots to a sinusoid with phase offset:½A _(pk-pk) sin(2πf _(c) t+φ), where A_(pk-pk) is the peak-to-peakamplitude, f_(c) is the cardiac frequency, t is time in seconds, and φis a phase off-set, and where f_(c) is cardiac frequency that is derivedfrom the subject's RBC amplitude oscillations.
 11. The method of claim10, wherein f_(c) is used in temporal fits of all other RBC spectralparameters (chemical shift, linewidth, and phase).
 12. The method ofclaim 1, further comprising normalizing the RBC amplitude spectralparameter, the barrier amplitude spectral parameter and the gasamplitude spectral parameter to a barrier-phase or gas-phase ¹²⁹Xesignal.
 13. The method of claim 1, further comprising, before thefitting and generating steps, pre-processing raw FIDs by FourierTransforming raw data along an indirect time domain with respect to abreath hold time period of the breath hold of the breathing maneuver,retaining only coefficients that exceed a defined threshold, thenFourier transforming back along an indirect frequency domain to providean FID with increased SNR relative to raw FIDs for the fitting tothereby filter non-dominant frequencies out of the indirect time domainto smooth temporal changes between different FIDs, while leavingspectral-frequency domain intact.
 14. The method of claim 13, furthercomprising using a FID sliding boxcar window filter and averaging aplurality of the time domain filtered FIDs to provide an FID withincreased SNR for the fitting.
 15. The method of claim 1, wherein theobtaining is at least partially in response to a pulse sequence with aTR in a range of 20 ms-300 ms, and a flip angle of about 20-90 degreesto thereby provide increased sensitivity to cardiogenic oscillations.16. The method of claim 1, wherein the obtaining is at least partiallyin response to a pulse sequence with a TR in a range of 200-300 ms and aflip angle in a range of 20-90 degrees.
 17. The method of claim 1,further comprising providing a plurality of defined different diseasepattern signatures of the ¹²⁹Xe spectral parameters correlated todifferent pulmonary hypertension and/or interstitial lung diseases. 18.The method of claim 17, further comprising electronically evaluating thegenerated ¹²⁹Xe spectral parameters to identify whether the subject hasone or more of the defined different disease pattern signatures.
 19. Themethod of claim 17, wherein one or more of the defined different diseasepatterns comprises oscillations of one or more of the RBC spectralparameters that exceeds a defined peak to peak threshold.
 20. The methodof claim 17, wherein one or more of the defined different diseasepatterns comprises oscillations of one or more of the RBC spectralparameters that is below a defined peak-to-peak threshold.
 21. Themethod of claim 17, wherein one or more of the defined different diseasepatterns is based on a shape of the oscillations of one or more of the¹²⁹Xe spectral parameters.
 22. The method of claim 17, wherein at leastone interstitial lung disease has a disease pattern signature comprisingan RBC frequency shift that decreases during the breath-hold of thebreathing maneuver relative to the inhale and/or exhale portion of thebreathing maneuver.
 23. The method of claim 17, wherein the defineddifferent disease patterns distinguish pre-capillary vascularobstruction by diminished RBC amplitude oscillations relative to adefined norm.
 24. The method of claim 17, wherein the defined differentdisease patterns distinguish post-capillary vascular disease frompre-capillary vascular disease by increased RBC amplitude oscillationsrelative to a defined norm.
 25. The method of claim 17, wherein one ormore of the defined different disease patterns can identify combinedpre- and post-capillary vascular disease, optionally by a shape of theRBC amplitude oscillations.
 26. The method of claim 1, furthercomprising comparing RBC amplitude oscillations of one or more RBC plotpre and post-administration of a pharmaceutical agent and identifyingvascular reactivity and/or change based on changes in RBC amplitudeoscillations.
 27. The method of claim 26, wherein the pharmaceuticalagent is a vasodilator.
 28. The method of claim 27, wherein thevasodilator is an inhaled vasodilator.
 29. The method of claim 26,wherein the pharmaceutical agent comprises prostacyclin.
 30. The methodof claim 1, further comprising comparing gas exchange ¹²⁹Xe MRI imagesof the subject to detect pulmonary hypertension associated withdiminished RBC transfer that affects a disproportionately largerfraction of the lung than can be explained by a fraction having abnormalbarrier uptake.
 31. The method of claim 1, wherein the obtained data isacquired between every 20 ms to every 300 ms during the breathingmaneuver, and wherein the breathing maneuver includes breath-hold, fullinspiration and full expiration over a time period of 10-30 seconds. 32.The method of claim 1, wherein the fitting is carried out with eachresonance characterized by 4 spectral parameters: amplitude (α),frequency (f), phase (φ), and Lorentzian linewidth (FWHM), and, for thebarrier resonance, a 5^(th) parameter, a Gaussian linewidth (FWHM_(G)),is also extracted, wherein the fitting is carried out with the barrierresonance initialized with equal Lorentzian and Gaussian linewidths, andwherein the fitting is carried out using the below equation:$\begin{matrix}{s_{fit} = {{a_{rbc}e^{{i\; \phi_{r\; {bc}}} + {2\; \pi \; {if}_{rbc}t}}e^{{- \pi}\; t \times {FWHM}_{rbc}}} + {a_{bar}e^{{i\; \phi_{bar}} + {2\; \pi \; {if}_{bar}t}}e^{{- \pi}\; t \times {FWHM}_{bar}}e^{{- 4}\; l\; n\; 2 \times t^{2}{FWHM}_{G_{bar}^{2}}}} + {a_{gas}e^{{i\; \phi_{gas}} + {2\; \pi \; i\; f_{gas}t}}e^{{- \pi}\; t\; \times {FWHM}_{gas}}}}} & {{EQN}(1)}\end{matrix}$
 33. The method of claim 17, further comprising identifyingwhether the subject has IPF, wherein IPF is characterized by a diseasesignature pattern with RBC amplitude oscillations that are significantlylarger (at least about 1.5× larger) than a healthy cohort, and whereinthe RBC frequency (chemical shift/ppm) and phase oscillations are atleast 2× above a healthy cohort.
 34. The method of claim 33, wherein theRBC amplitude variations are at least 1.5 fold greater than a healthycohort (optionally 16.8±5.2% vs 9.7±2.9%; P=0.008), the chemical shiftoscillations are more than 5-fold higher than the healthy cohort(optionally 0.43±0.33 ppm vs 0.083±0.05 ppm; P<0.001), and the RBC phaseoscillations are more than 5-fold higher than the healthy cohort(optionally 7.7±5.6° vs 1.4±0.8°; P<0.001).
 35. The method of claim 1,further comprising transmitting the obtained data from an imaging sitewith an MR Scanner to a remote server, wherein the remote serverperforms the fitting and generating actions, and wherein the remoteserver comprises or is in communication with a database of defineddifferent disease pattern signatures of the ¹²⁹Xe spectral parameterscorrelated to pulmonary hypertension and interstitial lung diseases. 36.The method of claim 17, wherein IPF is characterized by a diseasesignature pattern comprising an RBC chemical shift (ppm) that is below217 ppm.
 37. The method of claim 1, further comprising: obtaining aplurality of ¹²⁹Xe imaging parameters of the lung or lungs of thesubject including at least two of RBC defect percentage, ventilationdefect percentage and barrier defect percentage; and identifying whetherthe patient has a cardiopulmonary disease based on the obtained ¹²⁹Xeimaging parameters and at least two of the plurality of the dynamic¹²⁹Xe spectral parameters.
 38. An MRI scanner system, comprising: an MRIscanner; and at least one processor in communication with the MRIscanner and configured to carry out the method of claim
 1. 39. A medicalevaluation system comprising a server in communication with at least oneMRI scanner and having at least one processor that carries out themethod of claim
 1. 40. A method of identifying a cardiopulmonary diseaseof a patient, comprising: obtaining a plurality of ¹²⁹Xe imagingparameters including red blood cell (RBC) defect percentage, ventilationdefect percentage and barrier defect percentage; obtaining a pluralityof ¹²⁹Xe dynamic spectroscopy parameters including RBC shift oscillationand RBC amplitude oscillation; and identifying whether the patient has acardiopulmonary disease based on the obtained ¹²⁹Xe imaging parametersand the ¹²⁹Xe dynamic spectroscopy parameters.
 41. The method of claim40, further comprising generating a graphic signature of patientcardiopulmonary health or disease state based on the obtained ¹²⁹Xeimaging parameters and the ¹²⁹Xe dynamic spectroscopy parameters, thenidentifying whether the patient has a cardiopulmonary disease based onthe generated graphic signature.
 42. The method of claim 41, furthercomprising comparing the generated graphic signature to a library ofgraphic signatures which comprises unique graphic signatures for eachof: chronic obstructive pulmonary disease (COPD), idiopathic pulmonaryfibrosis (IPF), left heart failure (LHF), and pulmonary arterialhypertension (PAH).
 43. The method of claim 40, further comprisingproviding a diagnostic model that defines a likelihood of differentdiseases based on respective different thresholds of peaks of RBCoscillation and peaks of chemical shift (ppm) oscillation, and whereinthe identifying is carried out using the provided diagnostic model. 44.An MRI scanner system, comprising: an MRI scanner; and at least oneprocessor in communication with the MRI scanner and configured to carryout the method of claim
 40. 45. A medical evaluation system comprising aserver in communication with at least one MRI scanner and having atleast one processor that carries out the method of claim
 40. 46. Themethod of claim 1, wherein, before the obtaining step, the methodfurther comprises providing gas phase hyperpolarized ¹²⁹Xe to thesubject.